Re: [R] Stratifying level-1 variance with lmer()
David Afshartous med.miami.edu> writes: > I've fit some models via lme() and now I'm trying to fit similar models with > lmer() for some simulations I'm running. > > The model below (fm1) has an intercept variance that depends on treatment > group. How would one accomplish a similar stratification for the level-1 > variance, i.e., the within-group or patient variance? > > With lme() I was able to do this via: > update(fm1, > weights = varIdent(form = ~ 1 | treatment.ind) ) > > However, this does not work for lmer(). Is there any way around this? This is not yet implemented. See Douglas Bates' http://article.gmane.org/gmane.comp.lang.r.lme4.devel/518 Dieter __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to generate table output of a series of lm's
Martin Elff sowi.uni-mannheim.de> writes: > > modco <- list( > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz), > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, > subset=sector!="X"), > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, > subset=sector!="A"), > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, > subset=sector=="A"), > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, > subset=sector=="M") > ) > > sapply(modco,function(x) coef(summary(x))) This works, but consider if lm(normskvop ~ I(nts^0.5)-1+sector, data = colo,weights=wtz), is a better approach anyway. Dieter __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
Hello Spencer,
splendid. Please go ahead. I am wondering if one should return the lm-object
too and not only the htest-object. The benefit would be, that
summary(lm-object) would return the mentioned F-test in the R-Help thread too,
or one can return just the F-test result as a separate list element. If so, a
more appropriate function name would be archtest().
What do you think?
Best,
Bernhard
Dr. Bernhard Pfaff
International Structured Products Group
Director
Invesco Asset Management Deutschland GmbH
Bleichstrasse 60-62
D-60313 Frankfurt am Main
Tel: +49(0)69 29807 230
Fax: +49(0)69 29807 178
Email: [EMAIL PROTECTED]
Geschäftsführer: Karl Georg Bayer, Bernhard Langer, Dr. Jens Langewand,
Alexander Lehmann, Christian Puschmann
Handelsregister: Frankfurt am Main, HRB 28469
Sitz der Gesellschaft: Frankfurt am Main
>-Ursprüngliche Nachricht-
>Von: Spencer Graves [mailto:[EMAIL PROTECTED]
>Gesendet: Mittwoch, 6. Februar 2008 05:02
>An: Pfaff, Bernhard Dr.
>Cc: tom soyer; r-help@r-project.org
>Betreff: Re: AW: [R] ARCH LM test for univariant time series
>
>Dear Bernhard:
>
> Thanks very much. Unless you object, I shall add it to the
>'FinTS' library as "ArchTest" (comparable to the S-PLUS Finmetrics
>'archTest' function) -- with a worked example in '\scripts\ch03.R'.
>
> Best Wishes,
> Spencer
>
>Pfaff, Bernhard Dr. wrote:
>> Dear All,
>>
>>
>> one can visually inspect ARCH-effects by plotting acf/pacf of the
>> squared residuals from an OLS-estimation. This can be as simple as a
>> demeaned series. Further one can run an auxiliary regression by
>> regressing q lagged squared values and a constant on the
>squared series
>> itself. This test statistic (N-q)*R^2 is distributed as chisq with q
>> degrees of freedom.
>>
>> Something along the lines:
>>
>> archlmtest <- function (x, lags, demean = FALSE)
>> {
>> x <- as.vector(x)
>> if(demean) x <- scale(x, center = TRUE, scale = FALSE)
>> lags <- lags + 1
>> mat <- embed(x^2, lags)
>> arch.lm <- summary(lm(mat[, 1] ~ mat[, -1]))
>> STATISTIC <- arch.lm$r.squared * length(resid(arch.lm))
>> names(STATISTIC) <- "Chi-squared"
>> PARAMETER <- lags - 1
>> names(PARAMETER) <- "df"
>> PVAL <- 1 - pchisq(STATISTIC, df = PARAMETER)
>> METHOD <- "ARCH LM-test"
>> result <- list(statistic = STATISTIC, parameter = PARAMETER,
>> p.value = PVAL, method = METHOD, data.name =
>> deparse(substitute(x)))
>> class(result) <- "htest"
>> return(result)
>> }
>>
>> should work and yield equal results as mentioned earlier in
>this thread.
>>
>> Best,
>> Bernhard
>>
>>
>>
>>> Spencer,
>>>
>>> The warning message is sent from VAR, it basically lets you
>>> know that the
>>> data it used had no column names and it had to supply them
>>> using y1, y2, y3,
>>> etc. It can be suppressed by including options(warn=-1) in the
>>> function.
>>>
>>> Anyway, it seems that the p value from my function does not match
>>> FinMetrics'. I guess the function doesn't work... hmm...
>>>
>>>
>>> On 2/2/08, Spencer Graves <[EMAIL PROTECTED]> wrote:
>>>
Dear Tom:
Your revised function eliminates the discrepancy in the
>>> degrees of
>>>
freedom but is still very different from the numbers reports
>>> on Tsay, p.
>>>
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
Warning message:
In VAR(s, p = 1, type = "const") :
No column names supplied in y, using: y1, y2, y3, y4, y5,
>y6, y7, y8,
y9, y10, y11, y12 , instead.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
> Spencer,
>
> Sorry, I forgot that the default lag in arch is 16. Here
>
>>> is the fix. Can
>>>
you
> try it again and see if it gives the correct (or at least similar
>
compared
> to a true LM test) result?
>
> archTest=function(x, lags=12){
> #x is a vector
> require(vars)
> s=embed(x,lags)
> y=VAR(s,p=1,type="const")
> result=arch(y,lags.single=lags,multi=F)$arch.uni[[1]]
> return(result)
> }
>
> Thanks and sorry about the bug.
>
>
> On 2/2/08, Spencer Graves <[EMAIL PROTECTED]> wrote:
>
>
>> Dear Tom, Bernhard, Ruey:
>>
>> I can't get that to match Tsay's example, but I have other
>> questions about that.
>>
>> 1. I got the following using Tom's 'archTest'
>>
>>> function (below):
>>>
>>
>>> archTest(log(1+as.numeric(m.intc7303)), lags=12)
>>>
>>>
>>ARCH test (univariate)
>>
>> data: Residu
Re: [R] maps and lattice
Hi,
I use the spplot function from the sp package, it uses lattice to make
spatial plots. The sp-package provides spatial classes for R. See
http://r-spatial.sourceforge.net/ for more information on the use of
spatial data in R, http://r-spatial.sourceforge.net/gallery/ gives a
gallery of spatial plots with the R code it was created by. For
questions on spatial data in R the r-sig-geo mailing list is also a good
option (https://stat.ethz.ch/mailman/listinfo/r-sig-geo).
hope this helps!
Paul
Jon Loehrke wrote:
> Is it possible to place maps onto lattice plots?
>
> With basic plotting you can add a map to a plot
>
> library(lattice)
> long<-c(-69.2, -69.5, -70.1, -70.3)
> lat<-c(41, 41.5, 43.2, 42.8)
> plot(long, lat)
> map('state', c("massachusetts"),add=TRUE)
>
> but is it possible with lattice?
>
>
> library(lattice)
> factor<-c(1,1,2,2)
> xyplot(lat~long|fact)
> ...now what?
>
> I have looked at panel and found through google an extravagant shape
> file export/import to R.
> Is there a simpler fix?
>
> Thank you very much for your help.
>
> Jon
>
> School for Marine Science and Technology
> UMASS-Dartmouth
>
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Drs. Paul Hiemstra
Department of Physical Geography
Faculty of Geosciences
University of Utrecht
Heidelberglaan 2
P.O. Box 80.115
3508 TC Utrecht
Phone: +31302535773
Fax:+31302531145
http://intamap.geo.uu.nl/~paul
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Re: [R] How to generate table output of a series of lm's
On Wednesday 06 February 2008 (09:34:53), Dieter Menne wrote: > Martin Elff sowi.uni-mannheim.de> writes: > > modco <- list( > > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz), > > lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, > > subset=sector!="X"), lm(normskvop ~ I(nts^0.5)-1, data = > > colo,weights=wtz, subset=sector!="A"), lm(normskvop ~ I(nts^0.5)-1, data > > = colo,weights=wtz, subset=sector=="A"), lm(normskvop ~ I(nts^0.5)-1, > > data = colo,weights=wtz, subset=sector=="M") ) > > > > sapply(modco,function(x) coef(summary(x))) > > This works, but consider if > > lm(normskvop ~ I(nts^0.5)-1+sector, data = colo,weights=wtz), > > is a better approach anyway. Hmm. Maybe if Daniel intended to do: # Note now it is sector=="A" instead of sector!="A" modco <- list( lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, subset=sector=="X"), lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, subset=sector=="A"), lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, subset=sector=="A"), lm(normskvop ~ I(nts^0.5)-1, data = colo,weights=wtz, subset=sector=="M") ) But in that case lm(normskvop ~ sector/I(nts^0.5), data = colo,weights=wtz) or lm(normskvop ~ sector/I(nts^0.5) - sector, data = colo,weights=wtz) would be the "better" approach. Martin __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] 3D correlation
On Wednesday 06 February 2008 (01:35:15), [EMAIL PROTECTED] wrote: > how to generate correlated data which is correlated in three variables?? # Your correlation matrix S <- rbind( c(1,.3,.3), c(.3,1,.3), c(.3,.3,1) ) # Three independent normal variates x1 <- rnorm(1000) x2 <- rnorm(1000) x3 <- rnorm(1000) # Using the cholesky decomposition of S Y <- cbind(x1,x2,x3)%*%chol(S) # Three correlated normal variates y1 <- Y[,1] y2 <- Y[,2] y3 <- Y[,3] # Check cor(Y) There may be more elegant and general solutions and you can also use package "mvtnorm" to get correlated normal (or t) variates. But the principle comes down to this. Hope that helps, Martin __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Histogram/Bar plot graph
Hi, I have the following data: > Myvalues Gene ES MEF Embryo ESHyp 1 GeneA -0.38509507 0.00 1.6250 1.7039921 2 GeneB0.06262914 0.00 1.6250 -0.272033 and so on... I want to plot the expression values of GeneA and GeneB in the different cell/embryo/conditions (columns 2:5 above). Now, if I do: >library(ggplot2) > qplot(x=Gene, Embryo, geom = "bar") I get a plot of GeneA, B...so on only for the Embryo (ie column 4). How do I get to plot multiple instances of Y for the same value of X ? I have tried to find this out myself, but it is a bit confusing and so, I am writing to the list as a last resort. Any help or guidance will be much appreciated. TIA, Senthil __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] inserting text lines in a dat frame
> I am trying to prepare a bed file to load as accustom track on the
> UCSC genome browser.
> I have a data frame that looks like the one below.
> > x
> V1V2 V3
> 1 chr1 11255 55
> 2 chr1 11320 29
> 3 chr1 11400 45
> 4 chr2 21680 35
> 5 chr2 21750 84
> 6 chr2 21820 29
> 7 chr2 31890 46
> 8 chr3 32100 29
> 9 chr3 52380 29
> 10 chr3 66450 46
> I would like to insert the following 4 lines at the beginning:
> browser position chr1:1-1
> browser hide all
> track type=wiggle_0 name=sample description=chr1_sample visibility=full
> variableStep chrom=chr1 span=1
> and then insert 2 lines before each chromosome:
> track type=wiggle_0 name=sample description=chr2_sample visibility=full
> vriableStep chrom=chr2 span=1
> The final result should be tab delimited file that looks like this:
> browser position chr1:1-1
> browser hide all
> track type=wiggle_0 name=sample description=chr1_sample visibility=full
> variableStep chrom=chr1 span=1
> chr1 11255 55
> chr1 11320 29
> chr1 11400 45
> track type=wiggle_0 name=sample description=chr2_sample visibility=full
> variableStep chrom=chr2 span=1
> chr2 21680 35
> chr2 21750 84
> chr2 21820 29
> track type=wiggle_0 name=sample description=chr3_sample visibility=full
> variableStep chrom=chr3 span=1
> chr3 32100 29
> chr3 32170 45
> chr3 32240 45
#First write your preamble text to a file
preamble <- c("browser position chr1:1-1",
"browser hide all",
"track type=wiggle_0 name=sample description=chr1_sample
visibility=full",
"variableStep chrom=chr1 span=1")
write(preamble, "myfile.txt")
#Now split your data frame up by the values in V1
x <- data.frame(V1=rep(c("chr1", "chr2", "chr3"),times=c(3,4,3)),
V2=c(11255,11320,11400,21680,21750,21820,21890,32100,52380,66450),V3=c(55,29,45,35,84,29,46,29,29,46))
spx <- split(x, x$V1)
#Create lines of text to go before each piece of data frame
lV1 <- levels(x$V1)
maintext <- paste("track type=wiggle_0 name=sample description=", lV1,
"_sample visibility=full\nvariableStep chrom=", lV1,
" span=1", sep="")
#Use a loop to write the pieces to the file
for(i in 1: nlevels(x$V1))
{
write(maintext[i], "myfile.txt", append=TRUE)
write.table(spx[[i]], "myfile.txt", append=TRUE, sep="\t",
quote=FALSE,
col.names=FALSE, row.names=FALSE)
}
Regards,
Richie.
Mathematical Sciences Unit
HSL
ATTENTION:
This message contains privileged and confidential inform...{{dropped:20}}
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Re: [R] Incomplete ouput with sink and split=TRUE
you could use the unix function 'script' before invoking the R
interpreter.
example session:
$ script
Script started, file is typescript
[x86_64|[EMAIL PROTECTED]:~]
$ R --quiet --vanilla
> 1:10
[1] 1 2 3 4 5 6 7 8 9 10
> q()
[x86_64|[EMAIL PROTECTED]:~]
$ exit
exit
Script done, file is typescript
contents of file typescript:
===
Script started on Tue Feb 5 19:01:32 2008
[x86_64|[EMAIL PROTECTED]:~]
$ R --quiet --vanilla
> 1:10
[1] 1 2 3 4 5 6 7 8 9 10
> q()
[x86_64|[EMAIL PROTECTED]:~]
$ exit
exit
Script done on Tue Feb 5 19:01:45 2008
[x86_64|[EMAIL PROTECTED]:~]
-Alex
On 5 Feb 2008, at 16:12, jiho wrote:
> Dear List,
>
> I am trying to get R's terminal output to a file and to the terminal
> at the same time, so that I can walk through some tests and keep a log
> concurrently. The function 'sink' with the option split=TRUE seems to
> do just that. It works fine for most output but for objects of class
> htest, the terminal output is incomplete (the lines are there but
> empty). Here is an example session which shows the problem:
>
>> sink("textout.txt", type="output", split=T)
>> b=bartlett.test(runif(10),c(1,1,1,1,2,2,2,2,2,2))
>> class(b)
> [1] "htest"
>> b
>
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
>
>> t=t.test(runif(10),c(1,1,1,1,2,2,2,2,2,2))
>> t
>
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
> -1.5807338 -0.7316803
> sample estimates:
> mean of x mean of y
> 0.4437929 1.600
>
>> sink() # output in the file is complete
>> b
>
> Bartlett test of homogeneity of variances
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> Bartlett's K-squared = 0.9959, df = 1, p-value = 0.3183
>
>> t
>
> Welch Two Sample t-test
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> t = -5.7659, df = 16.267, p-value = 2.712e-05
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
> -1.5807338 -0.7316803
> sample estimates:
> mean of x mean of y
> 0.4437929 1.600
>
>>
>
> Is this a known bug (I'm using R 2.6.1 on OS X and Linux - FC8)? Is
> there an inherent reason why some portions of this output are not
> redirected?
>
> Thank you in advance for your help.
>
> JiHO
> ---
> http://jo.irisson.free.fr/
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Histogram/Bar plot graph
You'll need to transform your dataset in a long format first. library(ggplot2) n <- 5 MyValues <- data.frame(Gene = factor(LETTERS[seq_len(n)]), ES = rnorm(n), MEF = rnorm(n), Embrio = rnorm(n), EShyp = rnorm(n)) MyValuesMelt <- melt(MyValues, id.var = "Gene") ggplot(MyValuesMelt, aes(x = Gene, y = value, fill = variable)) + geom_bar(position = "dodge") ggplot(MyValuesMelt, aes(x = Gene, y = value)) + geom_bar(position = "dodge") + facet_grid(. ~ variable) HTH, Thierry ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 [EMAIL PROTECTED] www.inbo.be Do not put your faith in what statistics say until you have carefully considered what they do not say. ~William W. Watt A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions. ~M.J.Moroney -Oorspronkelijk bericht- Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Senthil Kumar M Verzonden: woensdag 6 februari 2008 11:19 Aan: r-help@r-project.org Onderwerp: [R] Histogram/Bar plot graph Hi, I have the following data: > Myvalues Gene ES MEF Embryo ESHyp 1 GeneA -0.38509507 0.00 1.6250 1.7039921 2 GeneB0.06262914 0.00 1.6250 -0.272033 and so on... I want to plot the expression values of GeneA and GeneB in the different cell/embryo/conditions (columns 2:5 above). Now, if I do: >library(ggplot2) > qplot(x=Gene, Embryo, geom = "bar") I get a plot of GeneA, B...so on only for the Embryo (ie column 4). How do I get to plot multiple instances of Y for the same value of X ? I have tried to find this out myself, but it is a bit confusing and so, I am writing to the list as a last resort. Any help or guidance will be much appreciated. TIA, Senthil __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Histogram/Bar plot graph
On Feb 6, 2008 2:35 AM, ONKELINX, Thierry <[EMAIL PROTECTED]> wrote: > You'll need to transform your dataset in a long format first. > > library(ggplot2) > n <- 5 > MyValues <- data.frame(Gene = factor(LETTERS[seq_len(n)]), ES = > rnorm(n), MEF = rnorm(n), Embrio = rnorm(n), EShyp = rnorm(n)) > MyValuesMelt <- melt(MyValues, id.var = "Gene") > ggplot(MyValuesMelt, aes(x = Gene, y = value, fill = variable)) + > geom_bar(position = "dodge") > ggplot(MyValuesMelt, aes(x = Gene, y = value)) + geom_bar(position = > "dodge") + facet_grid(. ~ variable) > Hi Thierry, Splendid! It is exactly what I wanted. Now, I am actually studying your reply to understand what those commands *actually* do. Thanks a lot, Sincerely Yours, Senthil __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] inserting text lines in a dat frame
Try this and see if it is what you want:
x <- read.table(textConnection(" V1V2 V3
1 chr1 11255 55
2 chr1 11320 29
3 chr1 11400 45
4 chr2 21680 35
5 chr2 21750 84
6 chr2 21820 29
7 chr2 31890 46
8 chr3 32100 29
9 chr3 52380 29
10 chr3 66450 46" ), header=TRUE)
cat("browser position chr1:1-1\nrowser hide all\n", file='tempxx.txt')
result <- lapply(split(x, x$V1), function(.chro){
cat(sprintf("track type=wiggle_0 name=sample description=%s_sample
visibility=full\nvariableStep chrom=%s span=1\n",
as.character(.chro$V1[1]), as.character(.chro$V1[1])),
file="tempxx.txt", append=TRUE)
write.table(.chro, sep="\t", file="tempxx.txt", append=TRUE,
col.names=FALSE, row.names=FALSE)
})
On Feb 5, 2008 11:22 PM, joseph <[EMAIL PROTECTED]> wrote:
>
>
>
>
>
> Hi Jim
> I am trying to prepare a bed file to load as accustom track on the UCSC
> genome browser.
> I have a data frame that looks like the one below.
> > x
> V1V2 V3
> 1 chr1 11255 55
> 2 chr1 11320 29
> 3 chr1 11400 45
> 4 chr2 21680 35
> 5 chr2 21750 84
> 6 chr2 21820 29
> 7 chr2 31890 46
> 8 chr3 32100 29
> 9 chr3 52380
> 29
> 10 chr3 66450 46
> I would like to insert the following 4 lines at the beginning:
> browser position chr1:1-1
> browser hide all
> track type=wiggle_0 name=sample description=chr1_sample visibility=full
> variableStep chrom=chr1 span=1
> and then insert 2 lines before each chromosome:
> track type=wiggle_0 name=sample description=chr2_sample visibility=full
> vriableStep chrom=chr2 span=1
> The final result should be tab delimited file that looks like this:
> browser position chr1:1-1
> browser hide all
> track type=wiggle_0 name=sample description=chr1_sample visibility=full
> variableStep chrom=chr1 span=1
> chr1 11255 55
> chr1 11320 29
> chr1 11400 45
> track type=wiggle_0 name=sample description=chr2_sample visibility=full
> variableStep chrom=chr2 span=1
> chr2 21680 35
> chr2 21750 84
> chr2 21820 29
> track type=wiggle_0 name=sample description=chr3_sample visibility=full
> variableStep chrom=chr3
> span=1
> chr3 32100 29
> chr3 32170 45
> chr3 32240 45
> Any kind of help or guidance will be much appreciated.
> Joseph
>
>
> Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it
> now.
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
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Re: [R] error message from apply()
Is 'thr' supposed to be the mean and sd of all the values in data2_1?
If so, then
thr <- mean(data2_1, na.rm=TRUE) + sd(data2_1,na.rm=TRUE)
I am not exactly sure of "what is the problem that you are trying to
solve". You just have to make sure that the object you are creating
by precomputing has the right structure to do what you want.
On Feb 6, 2008 12:56 AM, Stanley Ng <[EMAIL PROTECTED]> wrote:
> Now I understand why 3 by 3 data2_1 works and not the 3x10 data2_1.
>
> How can I precompute thr and pass it safely to function(x) for the column
> operation ?
>
>
> -Original Message-
> From: jim holtman [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, February 06, 2008 11:33
> To: Ng Stanley
> Cc: r-help
> Subject: Re: [R] error message from apply()
>
> You matrix only has 3 rows, so when you do 'apply(data2_1,2,...)' you are
> extracting columns which only have a length of 3 while thr has a length of
> 10
>
> > str(data2_1)
> num [1:3, 1:10] 0.958 0.271 -0.950 -0.130 -0.754 ...
> > str(thr)
> num [1:10] 1.060 0.528 0.104 0.925 -0.256 ...
> >
> That is why you get the error message of a size mismatch.
>
> On Feb 5, 2008 10:21 PM, Ng Stanley <[EMAIL PROTECTED]> wrote:
> > Replacing colMeans by mean removed the warning messages. Thanks
> >
> > However, when I precompute thr, and pass it to function(x), the error
> > returns. Using the shorter data2_1, doesn't give any warnings. What is
> > happening ?
> >
> > data2_1 <- matrix(c(0.9584190, 0.2710325, -0.9495618, -0.1301772,
> > -0.7539687, 0.5344464, -0.8205933, 0.1581723, -0.5351588, 0.04448065,
> > 0.9936430, 0.2278786, -0.8160700, -0.3314779, -0.4047975, 0.1168152,
> > -0.7458182, - 0.2231588, -0.5051651, -0.74871174, 0.9450363,
> > 0.4797723, -0.9033313, - 0.5825065, 0.8523742, 0.7402795, -0.7134312,
> > -0.8162558, 0.6345438, - 0.05704138), 3,10) # data2_1 <-
> > matrix(c(0.9584190, 0.2710325, -0.9495618, -0.1301772, - 0.7539687,
> > 0.5344464, -0.8205933, 0.1581723, -0.5351588), 3,3)
> >
> > thr <- colMeans(data2_1, na.rm = TRUE) + sd(data2_1, na.rm = TRUE)
> >
> > num <- apply(data2_1, 2, function(x) {
> >sum(x > (thr), na.rm = TRUE)
> > })
> >
> >
> >
> > On 2/6/08, jim holtman <[EMAIL PROTECTED]> wrote:
> > >
> > > The error message was coming from the call to colMeans where 'x' was
> > > not a matrix; it was a vector that resulted from the 'apply' call.
> > > Did you intend to use 'mean' instead like this example:
> > >
> > > > data2_1 <- matrix(c(0.9584190, 0.2710325, -0.9495618, -0.1301772,
> > > > -
> > > 0.7539687,
> > > + 0.5344464, -0.8205933, 0.1581723, -0.5351588, 0.04448065,
> > > + 0.9936430, 0.2278786, -0.8160700, -0.3314779, -0.4047975,
> > > + 0.1168152, -0.7458182, - 0.2231588, -0.5051651, -0.74871174,
> > > + 0.9450363, 0.4797723, -0.9033313, - 0.5825065, 0.8523742,
> > > + 0.7402795, -0.7134312, -0.8162558, 0.6345438, - 0.05704138), 3,10)
> > > >
> > > > num <- apply(data2_1, 2, function(x) {sum(x > (mean(x, na.rm =
> > > > TRUE) +
> > > + 1*sd(x, na.rm = TRUE)), na.rm = TRUE)})
> > > > num
> > > [1] 0 1 1 1 0 0 1 1 0 0
> > > >
> > >
> > >
> > > On Feb 5, 2008 8:43 PM, Ng Stanley <[EMAIL PROTECTED]> wrote:
> > > > Hi,
> > > >
> > > > I keep getting the error message. Please help.
> > > >
> > > > Error in colMeans(x, na.rm = TRUE) : 'x' must be an array of at
> least
> > > two
> > > > dimensions
> > > >
> > > > The codes are:
> > > >
> > > > data2_1 <- matrix(c(0.9584190, 0.2710325, -0.9495618, -0.1301772,
> > > > -
> > > 0.7539687,
> > > > 0.5344464, -0.8205933, 0.1581723, -0.5351588, 0.04448065,
> > > > 0.9936430, 0.2278786, -0.8160700, -0.3314779, -0.4047975,
> > > > 0.1168152, -0.7458182, - 0.2231588, -0.5051651, -0.74871174,
> > > > 0.9450363, 0.4797723, -0.9033313, - 0.5825065, 0.8523742,
> > > > 0.7402795, -0.7134312, -0.8162558, 0.6345438, - 0.05704138), 3,10)
> > > >
> > > > num <- apply(data2_1, 2, function(x) {sum(x > (colMeans(x, na.rm =
> > > > TRUE)
> > > +
> > > > 1*sd(x, na.rm = TRUE)), na.rm = TRUE)})
> > > >
> > > >[[alternative HTML version deleted]]
> > > >
> > > > __
> > > > R-help@r-project.org mailing list
> > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > PLEASE do read the posting guide
> > > http://www.R-project.org/posting-guide.html
> > > > and provide commented, minimal, self-contained, reproducible code.
> > > >
> > >
> > >
> > >
> > > --
> > > Jim Holtman
> > > Cincinnati, OH
> > > +1 513 646 9390
> > >
> > > What is the problem you are trying to solve?
> > >
> >
> >[[alternative HTML version deleted]]
> >
> > __
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>
>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 646 9390
>
> What is the problem you are trying to solve?
>
> _
[R] Multivariate Maximum Likelihood Estimation
Hi, I am trying to perform Maximum Likelihood estimation of a Multivariate model (2 independent variables + intercept) with autocorrelated errors of 1st order (ar(1)). Does R have a function for that? I could only find an univariate option (ar.mle function) and when writing my own I find that it is pretty memory-consuming (and sometimes wrong) so there must be a better way. Thanks, KB __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to search for packages - wrap up!
Charilaos Skiadas-3 wrote: > > On Feb 5, 2008, at 10:37 AM, Monica Pisica wrote: > > But perhaps I am missing something very obvious? > > I thought the task views were located where they are (linked from the page that lists packages) as they summarise the available packages for the given topic. Neil -- View this message in context: http://www.nabble.com/Re%3A-How-to-search-for-packages---wrap-up%21-tp15297545p15306481.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Incomplete ouput with sink and split=TRUE
On 2008-February-06 , at 11:25 , Alex Brown wrote:
> you could use the unix function 'script' before invoking the R
> interpreter.
Thanks for the suggestion. It would work for some cases and I did not
know about this utility. But most of the time I just put a list of
commands in a .R file and source it to execute it. In this case the
transcript would only contain "source("whatever.R", print.eval=T)"
which won't be very informative :/. And in the case of sourcing, the
problem with disappearing text stays the same.
Thanks for you answer anyway.
JiHO
---
http://jo.irisson.free.fr/
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Re: [R] Multivariate Maximum Likelihood Estimation
I get this message: Error: could not find function "gls" (and also) Error: could not find function "lm.gls" Which package is that in? Thanks, KB > Have you tried gls()? > > > > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature > and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, > methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > [EMAIL PROTECTED] > www.inbo.be > > Do not put your faith in what statistics say until you have carefully > considered what they do not say. ~William W. Watt > A statistical analysis, properly conducted, is a delicate dissection of > uncertainties, a surgery of suppositions. ~M.J.Moroney > > -Oorspronkelijk bericht- > Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > Namens Konrad BLOCHER > Verzonden: woensdag 6 februari 2008 12:12 > Aan: r-help@r-project.org > Onderwerp: [R] Multivariate Maximum Likelihood Estimation > > Hi, > > I am trying to perform Maximum Likelihood estimation of a Multivariate > model (2 independent variables + intercept) with autocorrelated errors > of > 1st order (ar(1)). > > Does R have a function for that? I could only find an univariate option > (ar.mle function) and when writing my own I find that it is pretty > memory-consuming (and sometimes wrong) so there must be a better way. > > Thanks, > > KB > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to search for packages - wrap up!
hits=-2.6 tests=BAYES_00 X-USF-Spam-Flag: NO On Wed, 2008-02-06 at 03:23 -0800, Neil Shephard wrote: > > > Charilaos Skiadas-3 wrote: > > > > On Feb 5, 2008, at 10:37 AM, Monica Pisica wrote: > > > > But perhaps I am missing something very obvious? > > > > > > I thought the task views were located where they are (linked from the page > that lists packages) as they summarise the available packages for the given > topic. > > Neil Originally, that might have been the thinking behind locating the link on CRAN and not the R homepage. Another reason might have been to keep the number of menu options on the R homepage to a manageable number. A new user will come to the R homepage, go to CRAN via the link under download and from there see Packages and then be swamped by the huge number available. Having Task Views as a link on the R homepage would make these more visible. However, getting this working so that users don't swamp the CRAN master will be interesting. The Task Views themselves could be on r-project.org but looking at the packages linked from the Task Views should be done on one of the CRAN mirrors and how that is arranged could be more hassle than it is worth, just to give Task Views higher visibility on R homepage. G -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to search for packages - wrap up!
On Feb 6, 2008, at 6:23 AM, Neil Shephard wrote: > Charilaos Skiadas-3 wrote: >> >> On Feb 5, 2008, at 10:37 AM, Monica Pisica wrote: >> >> But perhaps I am missing something very obvious? > > I thought the task views were located where they are (linked from > the page > that lists packages) as they summarise the available packages for > the given > topic. That would make sense, and brings up the other point, that the package directory is nontrivial to find as well. I'm thinking here of someone who has not used R yet, but is considering it. One approach those people would take, it seems to me, is to go to the main page and look around at the links to see if there is any information that would help them decide if R is right for what they want it. They have not heard of packages, and have no idea that a lot of the functionality is in the packages. So they would look on the list on the left looking for something that "clicks", and none of the items there would. If they eventually decide to click on the CRAN link, they are now faced with a long list of mirrors, and no further explanation of what is behind that. If they have seen mirror systems elsewhere, they would immediately come to the conclusion that this page will simply lead to downloading the software, and dismiss it as not useful. Just reading Gavin's reply, and he makes a good point about the difficulties related to the CRAN master. But couldn't we simply have the links to packages from the task views send someone through the mirror list? I would imagine something like that should be doable. Or we could simply have the "Task Views" link on the main page send you to a mirrors list, with perhaps a one-line explanation on the top of why this part is necessary. But at least at that point the user has selected "Task Views" and is more certain that they are on the right track. Even better, this step could be even one step deeper, after the user has selected which task view they want to see. > Neil Haris Skiadas Department of Mathematics and Computer Science Hanover College __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Effect size of comparison of two levels of a factor in multiple linear regression
On Feb 4, 08:49 AM, Chuck Cleland wrote:
> On 2/3/2008 10:09 AM, Christoph Mathys wrote:
>> Dear R users,
>> I have a linear model of the kind
>> outcome ~ treatment + covariate
>> where 'treatment' is a factor with three levels ("0", "1", and "2"),
>> and the covariate is continuous. Treatments "1" and "2" both have
>> regression coefficients significantly different from 0 when using
>> treatment contrasts with treatment "0" as the baseline. I would now like
>> to determine effect sizes (akin to Cohen's d in a two-sample comparison)
>> for the comparison to baseline of treatments "1" and "2". I have
>> illustrated a way to do this in the reproducible example below and am
>> grateful for any comments on the soundness of what I'm doing. I have not
>> yet found a way to determine confidence intervals for the effect sizes
>> derived below and would appreciate tips on that.
>
> How about scaling the outcome by the residual standard error from the
> unstandardized model? For example:
Yes, that also works. It's actually what my simulation does implicitly
and what I should have done in the first place. It has the added benefit
that a confidence interval can be given. Thanks.
>
> library(MASS)
>
> cmat <- diag(3)
> diag(cmat) <- c(25,25,25)
>
> df <- data.frame(Y = c(mvrnorm(100, mu=c(10,30,40), Sigma=cmat,
> empirical=TRUE)), TX = factor(rep(c(0,1,2), each=100)))
>
> fm1 <- lm(Y ~ TX, data = df)
> fm2 <- lm(scale(Y, scale=summary(fm1)$sigma) ~ TX, data = df)
>
> summary(fm1)
>
> Call:
> lm(formula = Y ~ TX, data = df)
>
> Residuals:
> Min 1Q Median 3Q Max
> -12.7260 -3.5215 -0.1982 3.4517 12.1690
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 10. 0.5000 20.00 <2e-16 ***
> TX1 20. 0.7071 28.28 <2e-16 ***
> TX2 30. 0.7071 42.43 <2e-16 ***
> ---
> Signif. codes: 0 ???***??? 0.001 ???**??? 0.01 ???*??? 0.05 ???.??? 0.1
> ??? ??? 1
>
> Residual standard error: 5 on 297 degrees of freedom
> Multiple R-squared: 0.8627, Adjusted R-squared: 0.8618
> F-statistic: 933.3 on 2 and 297 DF, p-value: < 2.2e-16
>
> summary(fm2)
>
> Call:
> lm(formula = scale(Y, scale = summary(fm1)$sigma) ~ TX, data = df)
>
> Residuals:
> Min 1Q Median 3Q Max
> -2.54521 -0.70431 -0.03965 0.69034 2.43380
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) -3. 0.1000 -33.33 <2e-16 ***
> TX1 4. 0.1414 28.28 <2e-16 ***
> TX2 6. 0.1414 42.43 <2e-16 ***
> ---
> Signif. codes: 0 ???***??? 0.001 ???**??? 0.01 ???*??? 0.05 ???.??? 0.1
> ??? ??? 1
>
> Residual standard error: 1 on 297 degrees of freedom
> Multiple R-squared: 0.8627, Adjusted R-squared: 0.8618
> F-statistic: 933.3 on 2 and 297 DF, p-value: < 2.2e-16
>
> confint(fm2)
> 2.5 %97.5 %
> (Intercept) -3.530132 -3.136535
> TX1 3.721685 4.278315
> TX2 5.721685 6.278315
>
> I've never seen this approach before, and I'm not how it would work when
> the variances within groups are heterogeneous or one or more covariates are
> added to the model.
Strictly speaking, the approach breaks down when we don't have
homogeneity of variances across groups. But luckily, I have it in the
real data I'm looking at.
When covariates are added, one has to decide case by case what to do
about them, namely which model's sigma to standardize against.
Standardizing against the sigma of a model that includes a given
covariate implies looking at effect sizes in a population where that
covariate has a fixed value. On the other hand, standardizing against the
sigma of a model that does not include a given covariate implies looking
at effect sizes in a population where that covariate varies.
> hope this helps,
Sure did. Thanks again,
Christoph
--
Christoph Mathys, M.S.
Music and Neuroimaging Laboratory
Beth Israel Deaconess Medical Center
and Harvard Medical School
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Re: [R] Multivariate Maximum Likelihood Estimation
hits=-2.6 tests=BAYES_00
X-USF-Spam-Flag: NO
On Wed, 2008-02-06 at 12:45 +0100, Konrad BLOCHER wrote:
> I get this message:
>
> Error: could not find function "gls" (and also)
> Error: could not find function "lm.gls"
>
> Which package is that in?
RSiteSearch("gls", restrict = "functions")
Tells you the answer.
Now might be a good time to review R's search/help tools - details of
which are in a section in the Posting Guide. You'll save yourself a lot
of time in the long run if you do.
HTH
G
>
> Thanks,
>
> KB
>
> > Have you tried gls()?
> >
> >
> >
> >
> > ir. Thierry Onkelinx
> > Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> > and Forest
> > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> > methodology and quality assurance
> > Gaverstraat 4
> > 9500 Geraardsbergen
> > Belgium
> > tel. + 32 54/436 185
> > [EMAIL PROTECTED]
> > www.inbo.be
> >
> > Do not put your faith in what statistics say until you have carefully
> > considered what they do not say. ~William W. Watt
> > A statistical analysis, properly conducted, is a delicate dissection of
> > uncertainties, a surgery of suppositions. ~M.J.Moroney
> >
> > -Oorspronkelijk bericht-
> > Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
> > Namens Konrad BLOCHER
> > Verzonden: woensdag 6 februari 2008 12:12
> > Aan: r-help@r-project.org
> > Onderwerp: [R] Multivariate Maximum Likelihood Estimation
> >
> > Hi,
> >
> > I am trying to perform Maximum Likelihood estimation of a Multivariate
> > model (2 independent variables + intercept) with autocorrelated errors
> > of
> > 1st order (ar(1)).
> >
> > Does R have a function for that? I could only find an univariate option
> > (ar.mle function) and when writing my own I find that it is pretty
> > memory-consuming (and sometimes wrong) so there must be a better way.
> >
> > Thanks,
> >
> > KB
> >
> > __
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
Dr. Gavin Simpson [t] +44 (0)20 7679 0522
ECRC, UCL Geography, [f] +44 (0)20 7679 0565
Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/
UK. WC1E 6BT. [w] http://www.freshwaters.org.uk
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] advice requested re: building "good" system (R, SQL db) for handling large datasets
Hi Thomas I'm certainly no expert but thought I'd reply as I'm likely to be in a similar position soon. With regards versions of R I think you should always have the latest release version. This will mean upgrading at least every 6 months, but this shouldn't be too much of a problem. With OSs, you need to be aware that there is an upper limit to the amount of RAM than be handled (2-4 GB) with many. I think if you plan to use more than 4GB RAM, you should definitely consider 64-bit linux. I have no information or opinions as to which flavour of linux. With databases, one issue that might be relevant is whether you want to store data in tables (e.g. one table to store one data.frame) that can subsequently be manipulated in the DB, or to store R objects as R objects (e.g. as BLOBs). My situation is likely to be the later case, and one of my concerns is that many DBs have an upper limit of 2GB on BLOBs, and I might potentially have objects that are larger than this. Finally, you might get more response on database issues from R-sig-db than R-help. Best wishes Richard. Thomas Pujol wrote: > R-community, > Sometime during the next 12-months, I plan on configuring a new computer > system on which I will primarily run "R" and a SQL database (Microsoft SQL > Server, MySQL, Oracle, etc). My primary goal is to "optimize" the system for > R, and for passing data to and from R and the database. > > I work with large datasets, and therefore I "think" one of my most important > goals should be to maximize the amount of RAM that R can utilize effectively. > > I am seeking advice concerning the version of R, OS, processor, > hard-drive/storage configuration, database, etc. that I should consider. (I > am guessing that I should build a system with lots of RAM, and a Linux OS, > but am seeking advice from the R community.) If I choose Linux, does it > matter which version I use? Any opinion regarding implementing a > commercially supported version from a vendor such as Red Hat, Sun, etc? Is > any database particularly better at "exchanging" data with R? > > While cost is of course a consideration, it is probably a secondary > consideration to overall performance, reliability, and ease of ongoing > maintenance/support. > > Thanks! > > > - > > [[alternative HTML version deleted]] > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to search for packages - wrap up!
I'm not sure that this would make any difference to someone considering using R. Would they know what CRAN stands for? Probably not unless they've used CPAN or equivalent in the past. Would they know what a 'Task View' is? Again probably not as its not patently obvious what it is, it doesn't "click" (at least not to my mind if I take a step back from already knowing what a Task View is). I think the current set up with mirrors is fine, it only takes a few seconds to click on a mirror and find that it takes you to a page that isn't simply for downloading software. Discussions of how the R web-site can be improved/altered seem to crop up periodically on the list. At the end of the day someone (who?) has to make the changes to the site. R developers already sacrifice their own time to improving the software. If you want to see changes, then volunteer to (I presume) the R-core team and enter into dialogue with them. Neil On Feb 6, 2008 12:02 PM, Charilaos Skiadas <[EMAIL PROTECTED]> wrote: > > On Feb 6, 2008, at 6:23 AM, Neil Shephard wrote: > > > Charilaos Skiadas-3 wrote: > >> > >> On Feb 5, 2008, at 10:37 AM, Monica Pisica wrote: > >> > >> But perhaps I am missing something very obvious? > > > > I thought the task views were located where they are (linked from > > the page > > that lists packages) as they summarise the available packages for > > the given > > topic. > > That would make sense, and brings up the other point, that the > package directory is nontrivial to find as well. I'm thinking here of > someone who has not used R yet, but is considering it. One approach > those people would take, it seems to me, is to go to the main page > and look around at the links to see if there is any information that > would help them decide if R is right for what they want it. They have > not heard of packages, and have no idea that a lot of the > functionality is in the packages. > > So they would look on the list on the left looking for something that > "clicks", and none of the items there would. If they eventually > decide to click on the CRAN link, they are now faced with a long > list of mirrors, and no further explanation of what is behind that. > If they have seen mirror systems elsewhere, they would immediately > come to the conclusion that this page will simply lead to downloading > the software, and dismiss it as not useful. > > > Just reading Gavin's reply, and he makes a good point about the > difficulties related to the CRAN master. But couldn't we simply have > the links to packages from the task views send someone through the > mirror list? I would imagine something like that should be doable. > > Or we could simply have the "Task Views" link on the main page send > you to a mirrors list, with perhaps a one-line explanation on the top > of why this part is necessary. But at least at that point the user > has selected "Task Views" and is more certain that they are on the > right track. Even better, this step could be even one step deeper, > after the user has selected which task view they want to see. > > > Neil > > Haris Skiadas > Department of Mathematics and Computer Science > Hanover College > > > > > -- "Do you really need to send me the email I just sent to you?" - Me Email - [EMAIL PROTECTED] / [EMAIL PROTECTED] Website - http://slack.ser.man.ac.uk/ Photos - http://www.flickr.com/photos/slackline/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] advice requested re: building "good" system (R, SQL db) for handling large datasets
With databases, one issue that might be relevant is whether you want to > store data in tables (e.g. one table to store one data.frame) that can > subsequently be manipulated in the DB, or to store R objects as R > objects (e.g. as BLOBs). My situation is likely to be the later case, > and one of my concerns is that many DBs have an upper limit of 2GB on > BLOBs, and I might potentially have objects that are larger than this. R objects in blobs - I never thought about that. Could you elaborate on how to do something like that (I am using RMySQL)? Thanks Rainer Finally, you might get more response on database issues from R-sig-db > than R-help. > > Best wishes > > Richard. > > > Thomas Pujol wrote: > > R-community, > > Sometime during the next 12-months, I plan on configuring a new computer > system on which I will primarily run "R" and a SQL database (Microsoft SQL > Server, MySQL, Oracle, etc). My primary goal is to "optimize" the system > for R, and for passing data to and from R and the database. > > > > I work with large datasets, and therefore I "think" one of my most > important goals should be to maximize the amount of RAM that R can utilize > effectively. > > > > I am seeking advice concerning the version of R, OS, processor, > hard-drive/storage configuration, database, etc. that I should consider. (I > am guessing that I should build a system with lots of RAM, and a Linux OS, > but am seeking advice from the R community.) If I choose Linux, does it > matter which version I use? Any opinion regarding implementing a > commercially supported version from a vendor such as Red Hat, Sun, etc? Is > any database particularly better at "exchanging" data with R? > > > > While cost is of course a consideration, it is probably a secondary > consideration to overall performance, reliability, and ease of ongoing > maintenance/support. > > > > Thanks! > > > > > > - > > > > [[alternative HTML version deleted]] > > > > __ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- -- Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology (UCT) Plant Conservation Unit Department of Botany University of Cape Town Rondebosch 7701 South Africa [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to form a simple R package
Well, not exactly. package.skeleton() is very useful as a first step, but it does *not* create a package entirely. It turns out that in Windows, creating a package is very simple once you have downloaded all programs needed (e.g., perl) and you have your path configured exaclty, (exactly, exactly) as described in the document found at the link below. After running package.skeleton, you must still run Rcmd build, Rcmd check, and Rcmd install. http://cran.r-project.org/doc/manuals/R-admin.html#The-Windows-toolset > -Original Message- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Benilton Carvalho > Sent: Wednesday, February 06, 2008 2:33 AM > To: [EMAIL PROTECTED] > Cc: r-help@r-project.org > Subject: Re: [R] How to form a simple R package > > ?package.skeleton > > b > > On Feb 5, 2008, at 1:48 PM, [EMAIL PROTECTED] wrote: > > > Is there a function to form in one step (configure files > and install) > > a simple R package of consisting of one script file of R functions? > > > > For example in Windows: > > > > form.package(name="mypkg", rcodefile ="c:\misc\mypkg.r" ) > > > > Thank you for any comments. > > Giles > > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to search for packages - wrap up!
> A new user will come to the R homepage, go to CRAN via the link under > download and from there see Packages and then be swamped by the huge > number available. Having Task Views as a link on the R homepage would > make these more visible. I would think that a new user would see the download heading, then think - I don't want to download a cran (whatever that is) I want to downloaded R, and then continue to be confused for another 10 minutes until they ask their colleague down the hall for the sequence of 5 (cran -> mirror -> windows -> base -> R-2.6.1-win32.exe) clicks that they need to find the installer! It would be nice to automatically provide a link to the current version of R for the platform that the user is browsing from (see e.g. getfirefox.com). Automatic selection of a mirror would be just as desirable, although I still maintain it would be better to dump the mirror system entirely and move to a content delivery network (CDN). Hadley -- http://had.co.nz/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Mixed models quantile regression
There is no generally agreed upon notion of random effects for quantile regression applications. Insofar as one is willing to accept the idea that random effects are just "shrunken fixed effects" one can consider similar schemes in the QR context; one such is described in “Quantile Regression for Longitudinal Data,” J. of Multivariate Analysis, (2004), 91, 74-89. But there are many open questions, so this is not for the faint hearted and there is certainly no "official" code. url:www.econ.uiuc.edu/~rogerRoger Koenker email[EMAIL PROTECTED]Department of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678Champaign, IL 61820 On Feb 5, 2008, at 9:40 PM, Beth Strain wrote: > > Dear R, > I have a question concerning quantile regression models. > > I am using the quantile regression model to test the relationship > between > abalone and the percentage cover of algae etc at different sites and > depths. > > An example is > fit<-rq(abalone~%coversessileinvertebrates+factor(Depth) > +factor(Site),tau=0.7) > > In this model depth is fixed and site is random. My question is, is it > possible specify the fixed and random effects in this model. If so > could > someone please give me an example of how to write the code. > > I can;t seem to find any information in the R help. > Thanks in advance > Beth Strain > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Incomplete ouput with sink and split=TRUE
On 2/5/2008 11:12 AM, jiho wrote:
> Dear List,
>
> I am trying to get R's terminal output to a file and to the terminal
> at the same time, so that I can walk through some tests and keep a log
> concurrently. The function 'sink' with the option split=TRUE seems to
> do just that. It works fine for most output but for objects of class
> htest, the terminal output is incomplete (the lines are there but
> empty). Here is an example session which shows the problem:
stats:::print.htest() uses writeLines to write some of its output to
stdout(), and it looks as though sink(split=T) misses those bits.
I'll change print.htest to use cat(), but it is probably a sign of a
bigger problem in sink(), and it's too late in the schedule to touch
that for 2.6.2.
Duncan Murdoch
>
> > sink("textout.txt", type="output", split=T)
> > b=bartlett.test(runif(10),c(1,1,1,1,2,2,2,2,2,2))
> > class(b)
> [1] "htest"
> > b
>
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
>
> > t=t.test(runif(10),c(1,1,1,1,2,2,2,2,2,2))
> > t
>
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
> -1.5807338 -0.7316803
> sample estimates:
> mean of x mean of y
> 0.4437929 1.600
>
> > sink() # output in the file is complete
> > b
>
> Bartlett test of homogeneity of variances
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> Bartlett's K-squared = 0.9959, df = 1, p-value = 0.3183
>
> > t
>
> Welch Two Sample t-test
>
> data: runif(10) and c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2)
> t = -5.7659, df = 16.267, p-value = 2.712e-05
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
> -1.5807338 -0.7316803
> sample estimates:
> mean of x mean of y
> 0.4437929 1.600
>
> >
>
> Is this a known bug (I'm using R 2.6.1 on OS X and Linux - FC8)? Is
> there an inherent reason why some portions of this output are not
> redirected?
>
> Thank you in advance for your help.
>
> JiHO
> ---
> http://jo.irisson.free.fr/
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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[R] counting row repetitions without loop
Hi, I have a data frame consisting of coordinates on a 10*10 grid, i.e. > example x y 1 4 5 2 6 7 3 6 6 4 7 5 5 5 7 6 6 7 7 4 5 8 6 7 9 7 6 10 5 6 What I would like to do is return an 10*10 matrix consisting of counts at each position, so in the above example I would have a matrix where, for example, cell [4,5] contains 2 and [6,7] contains 3. At the moment I have implemented this using a for loop over the rows of the data frame, however the data frames I want to process are very long so the loop takes many minutes to complete. Can I do this in a more efficient way? Cheers, David This e-mail and any attachments may contain confidential, copyright and or privileged material, and are for the use of the intended addressee only. If you are not the intended addressee or an authorised recipient of the addressee please notify us of receipt by returning the e-mail and do not use, copy, retain, distribute or disclose the information in or attached to the e-mail. Any opinions expressed within this e-mail are those of the individual and not necessarily of Diamond Light Source Ltd. Diamond Light Source Ltd. cannot guarantee that this e-mail or any attachments are free from viruses and we cannot accept liability for any damage which you may sustain as a result of software viruses which may be transmitted in or with the message. Diamond Light Source Limited (company no. 4375679). Registered in England and Wales with its registered office at Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, United Kingdom __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] axis help
Hi, i'm having trouble with my x and y axis. The commands i'm using are
below. The problem is that the y axis starts at coordinate 0,1 and the x
axis starts at coordinate 0,0. As far as I know the y axis can't start at 0
(because it's log scaled) ,so I would like to position the x axis at 0,1 but
don't know how to do this. Could anyone advise?
Thanks
Rich
df3<-data.frame(x=c(10,11,115,12,13,14,16,17,18,21,22,23,24,26,27,28,29,3,30
,32,33,34,35,4,41,45,5,50,52,56,58,6,67,6738,68,7,8,9,),fq=c(8,11,1,2,4,4,2,
2,6,3,4,2,2,1,1,1,4,51,3,1,1,1,1,35,1,1,19,2,1,1,1,14,1,1,1,10,13,5,),fqcvd=
c(5,8,1,1,3,3,2,2,5,3,4,2,2,0,1,1,3,13,2,1,1,1,1,17,1,0,11,2,1,1,1,7,1,1,1,7
,7,1,),fqcan=c(1,1,0,2,1,1,1,0,3,0,2,0,1,0,1,0,1,4,2,1,1,0,0,4,1,1,2,2,0,1,0
,2,0,1,1,2,3,1,),fqnondis=c(8,11,1,2,4,4,2,2,6,3,4,2,2,1,1,1,4,50,3,1,1,1,1,
34,1,1,19,2,1,1,1,14,1,1,1,10,12,5,))
k3<-with(df3,rep(x,times=fq))
kcvd3<-with(df3,rep(x,times=fqcvd))
kcvd3<-c(kcvd3,rep(NA,times=length(k3)-length(kcvd3)))
kcan3<-with(df3,rep(x,times=fqcan))
kcan3<-c(kcan3,rep(NA,times=length(k3)-length(kcan3)))
knondis3<-with(df3,rep(x,times=fqnondis))
knondis3<-c(knondis3,rep(NA,times=length(k3)-length(knondis3)))
boxplot(kcvd3,kcan3,knondis3,log='y',
ylim=c(1,4000),at=c(0.5,0.6,0.7),boxwex= 0.05,axes=FALSE,col =
c("yellow","orange","red"))
axis(1,at=c(0,0.6,1.1,1.6,2.1,2.6,3.1,3.6),labels=c(0,3,4,5,6,7,8,NA))
axis(2)
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Re: [R] How to generate table output of t-test
There may be an easier way but you can extract the
desired values from the list values in t
str(t) to see the elements in t.
test <- matrix(c(1, 1,2,2), 2,2)
tt <- apply(test, 1, t.test)
ttable <- function(tlist) {
tframe <- data.frame(NULL)
for(i in 1:length(tlist)){
t.value <- tlist[[i]][1]
dfs <- tlist[[i]][2]
conf.int1 <- tlist[[i]]$conf.int[1]
conf.int2 <- tlist[[i]]$conf.int[2]
p.value <- tlist[[i]][3]
t.vect <- cbind(t.value, dfs, conf.int1, conf.int2,
p.value)
tframe <- rbind(tframe, t.vect)
}
}
myts <- ttable(tt) ; myts
--- Ng Stanley <[EMAIL PROTECTED]> wrote:
> Hi,
>
> Given
>
> test <- matrix(c(1, 1,2,2), 2,2)
> t <- apply(test, 1, t.test)
>
> How can I obtain a table of p-values, confidence
> interval etc, instead of
>
>
> [[1]]
>
> One Sample t-test
>
> data: newX[, i]
> t = 3, df = 1, p-value = 0.2048
> alternative hypothesis: true mean is not equal to 0
> 95 percent confidence interval:
> -4.853102 7.853102
> sample estimates:
> mean of x
> 1.5
>
>
> [[2]]
>
> One Sample t-test
>
> data: newX[, i]
> t = 3, df = 1, p-value = 0.2048
> alternative hypothesis: true mean is not equal to 0
> 95 percent confidence interval:
> -4.853102 7.853102
> sample estimates:
> mean of x
> 1.5
>
> [[alternative HTML version deleted]]
>
> __
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> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained,
> reproducible code.
>
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[R] wilderSum
Hi,
Can somebody tell me the formula for "?wilderSum" in TTR package? I mean how
are these calculated?
BR, Shubha
Shubha Karanth | Amba Research
Ph +91 80 3980 8031 | Mob +91 94 4886 4510
Bangalore * Colombo * London * New York * San José * Singapore *
www.ambaresearch.com
This e-mail may contain confidential and/or privileged i...{{dropped:13}}
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Re: [R] R-Commander - pie charts menu blinded out
John Fox wrote: > Dear Peter and Iksmax, > > To elaborate slightly, the Rcmdr tries to figure out which menu items are > appropriate in a given context, and as Peter says, requires that you have at > least one factor in the active dataset before activating the pie chart menu > item; only factors will be included in the pie-chart dialog variable list. I > suppose that this approach sometimes makes it more difficult than necessary > to do some things that people legitimately want to do, but the idea is to > protect students in introductory statistics courses -- the target audience > for the Rcmdr -- from doing foolish things. (If I were really "holier than > the prophet" I would have omitted pie charts entirely!) > > Perhaps stating the obvious: That remark was intended as tongue-in-cheek Apart from protecting people from doing foolish things (there's a famous quote about that, though), there's also the aspect that an interface gets simpler if you reduce the number of choices. So of course it is a valid design decision. -p -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
Thanks Gabor for illustrating the basics oop in R using S3. Maybe I didn't
have the right documents, but you example taught me more about oop in R than
everything else I read combined! Thanks for the tip on R.oo, I plan to check
it out later.
I have a few followup questions...
(1) how do I encapsulate the generics? i.e., if a class has 100 methods,
then does it mean 100 generics would be dumped in the global environment?
Or, is it possible to define a local environment and restrict the generics
from one class to a particular environment? But then how do you call the
generics from a special environment? Also, is it possible to inherit classes
across different environment?
(2) it seems that an R specific IDE would improve productivity dramatically
(maybe even necessary?) with respect to oop. Is there such an IDE and does
it work for oop? I recall a group (in Germany?) was working on it but I
can't remember where I read about it.
Thanks!
On 2/5/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
>
> This illustration uses S3. Note that functions do not modify their
> arguments
> so to modify an object we have to pass it to the method and then pass the
> object back. There is also another system called S4 which involves typing
> of arguments and there are packages proto and R.oo which provide different
> OO models.
>
>
> # define constructors for bicycle and mountainBike classes
> Bicycle <- function(cadence, gear, speed) structure(list(cadence =
> cadence, gear = gear, speed = speed), class = "bicycle")
> MountainBike <- function(cadence, gear, speed, seatHeight) {
> x <- Bicycle(cadence, gear, speed)
> x$seatHeight <- seatHeight
> class(x) <- c(class(x), "mountainBike")
> x
> }
>
> # define generic setCadence and then methods for each class
>
> setCadence <- function(x, cadence) UseMethod("setCadence")
> setCadence.bicycle <- function(x, cadence) { x$cadence <- cadence; x }
>
> # mountBike's setCadence method overrides bicycle's setCadence method
> setCadence.mountBike <- function(x, cadence) { x$cadence <- cadence + 1; x
> }
>
> # list the setCadence methods avialable
> methods(setCadence)
>
> # define a generic applyBrake and a "bicycle" method
> # mountainBike will inherit the bicycle method by default
> applyBrake <- function(x, decrement) UseMethod("applyBrake")
> applyBrake.bicycle <- function(x, decrement) { x$speed <- x$speed -
> decrement }
>
> # list the applyBrake methods available
> methods(applyBrake)
>
> b <- Bicycle(1, 2, 3)
> m <- MountainBike(4, 5, 6, 7)
> m <- applyBrake(m, 1)
>
>
> On Feb 5, 2008 8:21 AM, tom soyer <[EMAIL PROTECTED]> wrote:
> > Hi,
> >
> > I read section 5, oop, of the R lang doc, and I am still not sure I
> > understand how to build a class in R for oop. I thought that since I
> > understand the oop syntex of Java and VB, I am wondering if the R
> programmig
> > experts could help me out by comparing and contrasting the oop syntex in
> R
> > with that of Java. For example, the basic class structure in Java is
> like
> > this:
> >
> > public class Bicycle {
> >
> >// *the Bicycle class has three fields*
> >public int cadence;
> >public int gear;
> >public int speed;
> >
> >// *the Bicycle class has one constructor*
> >public Bicycle(int startCadence, int startSpeed, int startGear) {
> >gear = startGear;
> >cadence = startCadence;
> >speed = startSpeed;
> >}
> >
> >// *the Bicycle class has four methods*
> >public void setCadence(int newValue) {
> >cadence = newValue;
> >}
> >
> >public void setGear(int newValue) {
> >gear = newValue;
> >}
> >
> >public void applyBrake(int decrement) {
> >speed -= decrement;
> >}
> >
> >public void speedUp(int increment) {
> >speed += increment;
> >}
> >
> > }
> >
> > Could one of the R experts please illustrate the R class syntex for
> writing
> > the R equivalent of the Java Bicycle class above?
> >
> > Also, in Java, inheritance is done like this:
> >
> > public class MountainBike extends Bicycle {
> >
> >// *the MountainBike subclass has one field*
> >public int seatHeight;
> >
> >// *the MountainBike subclass has one constructor*
> >public MountainBike(int startHeight, int startCadence, int
> startSpeed,
> > int startGear) {
> >super(startCadence, startSpeed, startGear);
> >seatHeight = startHeight;
> >}
> >
> >// *the MountainBike subclass has one method*
> >public void setHeight(int newValue) {
> >seatHeight = newValue;
> >}
> >
> > }
> >
> > What would be the R oop syntex for inheritance in the case of the
> > MontainBike class?
> >
> > Thanks!
> >
> > --
> > Tom
> >
> >[[alternative HTML version deleted]]
> >
> > __
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and pro
Re: [R] Incomplete ouput with sink and split=TRUE
On 2008-February-06 , at 14:45 , Duncan Murdoch wrote: > On 2/5/2008 11:12 AM, jiho wrote: >> Dear List, >> I am trying to get R's terminal output to a file and to the >> terminal at the same time, so that I can walk through some tests >> and keep a log concurrently. The function 'sink' with the option >> split=TRUE seems to do just that. It works fine for most output >> but for objects of class htest, the terminal output is incomplete >> (the lines are there but empty). Here is an example session which >> shows the problem: > > stats:::print.htest() uses writeLines to write some of its output to > stdout(), and it looks as though sink(split=T) misses those bits. > > I'll change print.htest to use cat(), but it is probably a sign of a > bigger problem in sink(), and it's too late in the schedule to touch > that for 2.6.2. > > Duncan Murdoch Thank you for your attention on this. Given your comment I filed on a bug report on this (same subject that this email, no bug ID yet) JiHO --- http://jo.irisson.free.fr/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] counting row repetitions without loop
On Wednesday 06 February 2008 14:08, Waterman, DG (David) wrote: > Hi, > > I have a data frame consisting of coordinates on a 10*10 grid, i.e. > > > example > > x y > 1 4 5 > 2 6 7 > 3 6 6 > 4 7 5 > 5 5 7 > 6 6 7 > 7 4 5 > 8 6 7 > 9 7 6 > 10 5 6 > > What I would like to do is return an 10*10 matrix consisting of counts > at each position, so in the above example I would have a matrix where, > for example, cell [4,5] contains 2 and [6,7] contains 3. At the moment I > have implemented this using a for loop over the rows of the data frame, > however the data frames I want to process are very long so the loop > takes many minutes to complete. Can I do this in a more efficient way? > > Cheers, David, have a look at "mapply" (?mapply). This does what you need very quickly. J __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] counting row repetitions without loop
I think this does what you want, but there may be a more efficient way
x y
4 5
6 7
6 6
7 5
5 7
6 7
4 5
6 7
7 6
5 6
dat <- read.table('clipboard', header=TRUE) # copy sample data above
dat$patt <- paste(dat$x,dat$y, sep='')
mm <- as.data.frame(with(dat, table(patt)))
dat <- merge(dat, mm, by='patt')
mat <- matrix(0, ncol=10, nrow=10)
gg <- matrix(c(dat$x, dat$y), ncol=2)
mat[gg] <- dat$Freq
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Waterman,
> DG (David)
> Sent: Wednesday, February 06, 2008 9:08 AM
> To: r-help@r-project.org
> Subject: [R] counting row repetitions without loop
>
> Hi,
>
> I have a data frame consisting of coordinates on a 10*10 grid, i.e.
>
> > example
> x y
> 1 4 5
> 2 6 7
> 3 6 6
> 4 7 5
> 5 5 7
> 6 6 7
> 7 4 5
> 8 6 7
> 9 7 6
> 10 5 6
>
> What I would like to do is return an 10*10 matrix consisting
> of counts at each position, so in the above example I would
> have a matrix where, for example, cell [4,5] contains 2 and
> [6,7] contains 3. At the moment I have implemented this using
> a for loop over the rows of the data frame, however the data
> frames I want to process are very long so the loop takes many
> minutes to complete. Can I do this in a more efficient way?
>
> Cheers,
> David
> This e-mail and any
> attachments may contain confidential, copyright and or
> privileged material, and are for the use of the intended
> addressee only. If you are not the intended addressee or an
> authorised recipient of the addressee please notify us of
> receipt by returning the e-mail and do not use, copy, retain,
> distribute or disclose the information in or attached to the e-mail.
> Any opinions expressed within this e-mail are those of the
> individual and not necessarily of Diamond Light Source Ltd.
> Diamond Light Source Ltd. cannot guarantee that this e-mail
> or any attachments are free from viruses and we cannot accept
> liability for any damage which you may sustain as a result of
> software viruses which may be transmitted in or with the message.
> Diamond Light Source Limited (company no. 4375679).
> Registered in England and Wales with its registered office at
> Diamond House, Harwell Science and Innovation Campus, Didcot,
> Oxfordshire, OX11 0DE, United Kingdom
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] counting row repetitions without loop
Sorry, word wrap made that incomprehensible, I think
x y
4 5
6 7
6 6
7 5
5 7
6 7
4 5
6 7
7 6
5 6
dat <- read.table('clipboard', header=TRUE)
dat$patt <- paste(dat$x,dat$y, sep='')
mm <- as.data.frame(with(dat, table(patt)))
dat <- merge(dat, mm, by='patt')
mat <- matrix(0, ncol=10, nrow=10)
gg <- matrix(c(dat$x, dat$y), ncol=2)
mat[gg] <- dat$Freq
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Doran, Harold
> Sent: Wednesday, February 06, 2008 9:56 AM
> To: Waterman, DG (David); r-help@r-project.org
> Subject: Re: [R] counting row repetitions without loop
>
> I think this does what you want, but there may be a more efficient way
>
> x y
> 4 5
> 6 7
> 6 6
> 7 5
> 5 7
> 6 7
> 4 5
> 6 7
> 7 6
> 5 6
> dat <- read.table('clipboard', header=TRUE) # copy sample
> data above dat$patt <- paste(dat$x,dat$y, sep='') mm <-
> as.data.frame(with(dat, table(patt))) dat <- merge(dat, mm,
> by='patt') mat <- matrix(0, ncol=10, nrow=10) gg <-
> matrix(c(dat$x, dat$y), ncol=2) mat[gg] <- dat$Freq
>
> > -Original Message-
> > From: [EMAIL PROTECTED]
> > [mailto:[EMAIL PROTECTED] On Behalf Of Waterman, DG
> > (David)
> > Sent: Wednesday, February 06, 2008 9:08 AM
> > To: r-help@r-project.org
> > Subject: [R] counting row repetitions without loop
> >
> > Hi,
> >
> > I have a data frame consisting of coordinates on a 10*10 grid, i.e.
> >
> > > example
> > x y
> > 1 4 5
> > 2 6 7
> > 3 6 6
> > 4 7 5
> > 5 5 7
> > 6 6 7
> > 7 4 5
> > 8 6 7
> > 9 7 6
> > 10 5 6
> >
> > What I would like to do is return an 10*10 matrix
> consisting of counts
> > at each position, so in the above example I would have a
> matrix where,
> > for example, cell [4,5] contains 2 and [6,7] contains 3. At
> the moment
> > I have implemented this using a for loop over the rows of the data
> > frame, however the data frames I want to process are very
> long so the
> > loop takes many minutes to complete. Can I do this in a
> more efficient
> > way?
> >
> > Cheers,
> > David
> > This e-mail and any
> attachments may
> > contain confidential, copyright and or privileged material, and are
> > for the use of the intended addressee only. If you are not the
> > intended addressee or an authorised recipient of the
> addressee please
> > notify us of receipt by returning the e-mail and do not use, copy,
> > retain, distribute or disclose the information in or
> attached to the
> > e-mail.
> > Any opinions expressed within this e-mail are those of the
> individual
> > and not necessarily of Diamond Light Source Ltd.
> > Diamond Light Source Ltd. cannot guarantee that this e-mail or any
> > attachments are free from viruses and we cannot accept
> liability for
> > any damage which you may sustain as a result of software
> viruses which
> > may be transmitted in or with the message.
> > Diamond Light Source Limited (company no. 4375679).
> > Registered in England and Wales with its registered office
> at Diamond
> > House, Harwell Science and Innovation Campus, Didcot, Oxfordshire,
> > OX11 0DE, United Kingdom
> >
> > __
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] GLM coefficients
Dear all, After running a glm, I use the summary ( ) function to extract its coefficients and related statistics for further use. Unfortunately, the screen only displays a small (last) part of the results. I tried to overcome the problem by creating/saving an object "coef" for coefficients of the model and export/save it e.g. as a cvs document. While I succed with this operatiion, I do not manage to pick the standard deviations and other statistics associated with individual coefficients. What may I do to get the whole set of coefficients and associated statistics for my GLM? Thanks for your help. J. Munyandorero [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] scatterplot3d + box lines
Dear all; I've been trying to change the type of line used to draw the box around the 3d scatterplot (package scatterplot3d) from lty=1 to lty=2 without sucess. I would appreciate suggestions of how to do it. Thanks PM __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] scatterplot3d + box lines
On 2/6/2008 10:07 AM, Pedro Mardones wrote: > Dear all; > I've been trying to change the type of line used to draw the box > around the 3d scatterplot (package scatterplot3d) from lty=1 to lty=2 > without sucess. I would appreciate suggestions of how to do it. Use lty.axis=2. (This is mentioned on the help page, but there are a lot of parameters there, and I can see how you might have missed it.) Duncan Murdoch __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] GLM coefficients
If I understand correctly.. using the example in ?glm > utils::data(anorexia, package="MASS") > anorex.1 <- glm(Postwt ~ Prewt + Treat + offset(Prewt), family = gaussian, data = anorexia) > summ <- summary(anorex.1) Then check > names(summ) for the available objects. For coefficients standard errors and t-tests > summ$coefficients Again do this for any object other than "coefficients" you would want from names(summ). Best regards, Ioannis Kosmidis On 6 Feb 2008, at 15:06, Munyandorero, Joseph wrote: > Dear all, > > After running a glm, I use the summary ( ) function to extract its > coefficients and related statistics for further use. Unfortunately, > the > screen only displays a small (last) part of the results. I tried to > overcome the problem by creating/saving an object "coef" for > coefficients of the model and export/save it e.g. as a cvs document. > While I succed with this operatiion, I do not manage to pick the > standard deviations and other statistics associated with individual > coefficients. What may I do to get the whole set of coefficients and > associated statistics for my GLM? Thanks for your help. > > J. Munyandorero > > [[alternative HTML version deleted]] > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. === Dr Ioannis Kosmidis Department of Statistics , University of Warwick, Coventry, CV4 7AL, United Kingdom Email : [EMAIL PROTECTED] Home: http://go.warwick.ac.uk/kosmidis Voice : +44(0)2476 575754 Fax : +44(0)2476 524532 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] GLM coefficients
See this example: coef(summary(glm(Postwt ~ Prewt + Treat + offset(Prewt),family=gaussian, data=anorexia))) Is this you want? On 06/02/2008, Munyandorero, Joseph <[EMAIL PROTECTED]> wrote: > Dear all, > > After running a glm, I use the summary ( ) function to extract its > coefficients and related statistics for further use. Unfortunately, the > screen only displays a small (last) part of the results. I tried to > overcome the problem by creating/saving an object "coef" for > coefficients of the model and export/save it e.g. as a cvs document. > While I succed with this operatiion, I do not manage to pick the > standard deviations and other statistics associated with individual > coefficients. What may I do to get the whole set of coefficients and > associated statistics for my GLM? Thanks for your help. > > J. Munyandorero > > [[alternative HTML version deleted]] > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40" S 49° 16' 22" O __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] 3d scatterplot with error bars
Is there anyway to produce a 3D scatterplot with error bars in the x,y,z directions? I have searched around and know of scatterplot3d but did not see any way to put error bars on the points. Any ideas? __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
On Feb 6, 2008 9:45 AM, tom soyer <[EMAIL PROTECTED]> wrote:
> Thanks Gabor for illustrating the basics oop in R using S3. Maybe I didn't
> have the right documents, but you example taught me more about oop in R than
> everything else I read combined! Thanks for the tip on R.oo, I plan to check
> it out later.
>
> I have a few followup questions...
>
> (1) how do I encapsulate the generics? i.e., if a class has 100 methods,
> then does it mean 100 generics would be dumped in the global environment?
> Or, is it possible to define a local environment and restrict the generics
> from one class to a particular environment? But then how do you call the
> generics from a special environment? Also, is it possible to inherit classes
> across different environment?
Both ofthe following return 3. If that is not what you are asking
then I suggest you experiment with a few small examples of
this nature:
f <- function() {
F <- function(x) UseMethod("F")
F.default <- function(x) x
F(3)
}
F.default <- function(x) NULL
f()
F <- function(x) UseMethod("F")
f <- function() {
F.default <- function(x) x
F(3)
}
F.default <- function(x) NULL
f()
>
> (2) it seems that an R specific IDE would improve productivity dramatically
> (maybe even necessary?) with respect to oop. Is there such an IDE and does
> it work for oop? I recall a group (in Germany?) was working on it but I
> can't remember where I read about it.
>
> Thanks!
>
>
> On 2/5/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
> > This illustration uses S3. Note that functions do not modify their
> arguments
> > so to modify an object we have to pass it to the method and then pass the
> > object back. There is also another system called S4 which involves typing
> > of arguments and there are packages proto and R.oo which provide different
> > OO models.
> >
> >
> > # define constructors for bicycle and mountainBike classes
> > Bicycle <- function(cadence, gear, speed) structure(list(cadence =
> > cadence, gear = gear, speed = speed), class = "bicycle")
> > MountainBike <- function(cadence, gear, speed, seatHeight) {
> > x <- Bicycle(cadence, gear, speed)
> > x$seatHeight <- seatHeight
> > class(x) <- c(class(x), "mountainBike")
> > x
> > }
> >
> > # define generic setCadence and then methods for each class
> >
> > setCadence <- function(x, cadence) UseMethod("setCadence")
> > setCadence.bicycle <- function(x, cadence) { x$cadence <- cadence; x }
> >
> > # mountBike's setCadence method overrides bicycle's setCadence method
> > setCadence.mountBike <- function(x, cadence) { x$cadence <- cadence + 1; x
> }
> >
> > # list the setCadence methods avialable
> > methods(setCadence)
> >
> > # define a generic applyBrake and a "bicycle" method
> > # mountainBike will inherit the bicycle method by default
> > applyBrake <- function(x, decrement) UseMethod("applyBrake")
> > applyBrake.bicycle <- function(x, decrement) { x$speed <- x$speed -
> decrement }
> >
> > # list the applyBrake methods available
> > methods(applyBrake)
> >
> > b <- Bicycle(1, 2, 3)
> > m <- MountainBike(4, 5, 6, 7)
> > m <- applyBrake(m, 1)
> >
> >
> > On Feb 5, 2008 8:21 AM, tom soyer <[EMAIL PROTECTED]> wrote:
> > > Hi,
> > >
> > > I read section 5, oop, of the R lang doc, and I am still not sure I
> > > understand how to build a class in R for oop. I thought that since I
> > > understand the oop syntex of Java and VB, I am wondering if the R
> programmig
> > > experts could help me out by comparing and contrasting the oop syntex in
> R
> > > with that of Java. For example, the basic class structure in Java is
> like
> > > this:
> > >
> > > public class Bicycle {
> > >
> > >// *the Bicycle class has three fields*
> > >public int cadence;
> > >public int gear;
> > >public int speed;
> > >
> > >// *the Bicycle class has one constructor*
> > >public Bicycle(int startCadence, int startSpeed, int startGear) {
> > >gear = startGear;
> > >cadence = startCadence;
> > >speed = startSpeed;
> > >}
> > >
> > >// *the Bicycle class has four methods*
> > >public void setCadence(int newValue) {
> > >cadence = newValue;
> > >}
> > >
> > >public void setGear(int newValue) {
> > >gear = newValue;
> > >}
> > >
> > >public void applyBrake(int decrement) {
> > >speed -= decrement;
> > >}
> > >
> > >public void speedUp(int increment) {
> > >speed += increment;
> > >}
> > >
> > > }
> > >
> > > Could one of the R experts please illustrate the R class syntex for
> writing
> > > the R equivalent of the Java Bicycle class above?
> > >
> > > Also, in Java, inheritance is done like this:
> > >
> > > public class MountainBike extends Bicycle {
> > >
> > >// *the MountainBike subclass has one field*
> > >public int seatHeight;
> > >
> > >// *the MountainBike subclass has one constructor*
> > >public MountainBike(int startHeight, int startCadence, int
> startSpeed,
> > >
Re: [R] Inconsistent lattice scales$x$at, label behaviour for POSIXct
Here's a related problem that works for numeric but not for POSIXct
I am seeing it where a panel has no at labels, but others do.
This simple example only has one panel with no at labels.
> baseval = 0;
> xyplot(1:10 ~ (baseval + c(1:10)), scales=list(x=list
+ (at=list(c()), labels=list(c()), relation="free")), type="l")
(works)
baseval = as.POSIXct("2007-01-01");
> xyplot(1:10 ~ (baseval + c(1:10)), scales=list(x=list
+ (at=list(c()), labels=list(c()), relation="free")), type="l")
Error in as.POSIXct.default(at) :
do not know how to convert 'at' to class "POSIXlt"
(fails)
-Alex
On 5 Feb 2008, at 20:59, Deepayan Sarkar wrote:
> On 2/5/08, Alex Brown <[EMAIL PROTECTED]> wrote:
>> I have encountered the following behaviour in lattice in 2.6.1 (and
>> 2.4.0) which differs depending upon the type you use. I believe the
>> numeric behaviour to be correct, and the POSIXct behaviour to be in
>> error.
>>
>> When the x data and x axis in a lattice graph are POSIXct, and when
>> using scales$x$at and scales$x$labels to add custom labels:
>>
>> If the first visible at value is not the first specified at value
>> (due
>> to x limit settings), the first visible label nonetheless receives
>> the
>> first specified label, instead of the label corresponding to the
>> first
>> visible at.
>
> Yes, the relevant "POSIXct" method was subsetting 'at' to lie within
> the specified limits but not 'labels'. Should be fixed in the next
> update. Thanks,
>
> -Deepayan
>
>
>> In the following example, at = baseval + 1:4, label = letters[1:4]
>>
>> I have set it up so that baseval + 1:2 are not visible in the graph
>>
>> for numeric and Date types, the visible labels are letters[3:4] - ie
>> "c" "d"
>>
>> for POSIXct, the visible labels are letters[1:3] - "a" "b".
>>
>>
>> Simplest to show this by example:
>>
>> # numeric
>>
>> baseval=0;
>> xyplot(1:10 ~ (baseval + 1:10) , scales=list(x=list
>> (at=baseval+1:4, labels=letters[1:4])),xlim=baseval+c(3,10))
>>
>> # Date
>>
>> baseval = as.Date("2007-01-01");
>> xyplot(1:10 ~ (baseval + 1:10) , scales=list(x=list
>> (at=baseval+1:4, labels=letters[1:4])),xlim=baseval+c(3,10))
>>
>> # POSIXct
>>
>> baseval = as.POSIXct("2007-01-01");
>> xyplot(1:10 ~ (baseval + 1:10) , scales=list(x=list
>> (at=baseval+1:4, labels=letters[1:4])),xlim=baseval+c(3,10))
>>
>> in particular, compare the Date and POSIXct versions
>>
>> -Alex Brown
>>
>> __
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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[R] kinship package: drawing pedigree error
Hi
Im using the kinship package to draw a pedigree. On my data set this works fine
but when i add indivudals to the pedigree i keep getting an error i hope
someone can help me!
This is the code im using:
Data<-read.table("Tree.txt", header=T, sep=",")
attach(Data)
ped<-pedigree(id, dadid, momid, sex, aff)
par(xpd=T)
plot.pedigree(ped)
This is my data looks like without the last 3 individuals it works perfect,when
i add them i get the following error:
Error in if (min(pos2) < 0) { : missing value where TRUE/FALSE needed
famid,id,dadid,momid,sex,aff
1,8860,9972,8856,2,0
1,8855,9972,8856,2,0
1,8859,9976,8860,2,0
1,8854,9971,8855,2,0
1,8863,9975,8859,2,0
1,8858,9975,8859,2,0
1,8865,9975,8859,2,0
1,9969,9970,8854,1,0
1,8864,9980,8863,2,0
1,8862,9980,8863,2,0
1,23834,9981,8865,2,0
1,9968,9969,8853,1,0
1,21141,9974,8858,1,0
1,21142,9974,8858,2,0
1,23172,265,21142,2,0
1,25409,265,21142,1,0
1,23171,265,21142,2,0
1,265,NA,NA,1,0
1,9981,NA,NA,1,0
1,8853,NA,NA,2,0
1,9974,NA,NA,1,0
1,9980,NA,NA,1,0
1,9972,NA,NA,1,0
1,8856,NA,NA,2,0
1,9976,NA,NA,1,0
1,9971,NA,NA,1,0
1,9975,NA,NA,1,0
1,9970,NA,NA,1,0
1,9979,NA,NA,1,0
1,20644,9979,8862,2,0
1,20670,9979,8862,1,0
I tried putting nuclear families closer together in de pedigree but this
doesn't seem to help. All individuals have both parents in the pedigree or have
2 missing parents.
I hope someone can help me with this!
Iris
Never miss a thing. Make Yahoo your home page.
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Re: [R] Multivariate Maximum Likelihood Estimation
OK I got gls running but this is the error message that I got: > gls_results <- gls(LnWRPK ~ LnWGDP+LnWYIELD,correlation = corAR1) Error in switch(mode(x), "NULL" = structure(NULL, class = "formula"), : invalid formula Google didn't give any results unfortunately. Help! :) Thanks, KB > Have you tried gls()? > > > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > [EMAIL PROTECTED] > www.inbo.be > > Do not put your faith in what statistics say until you have carefully considered what they do not say. ~William W. Watt > A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions. ~M.J.Moroney > > -Oorspronkelijk bericht- > Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Konrad BLOCHER > Verzonden: woensdag 6 februari 2008 12:12 > Aan: r-help@r-project.org > Onderwerp: [R] Multivariate Maximum Likelihood Estimation > > Hi, > > I am trying to perform Maximum Likelihood estimation of a Multivariate model (2 independent variables + intercept) with autocorrelated errors of > 1st order (ar(1)). > > Does R have a function for that? I could only find an univariate option (ar.mle function) and when writing my own I find that it is pretty memory-consuming (and sometimes wrong) so there must be a better way. > > Thanks, > > KB > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Regression with time-dependent coefficients
Hi, I was wondering if someone might be willing to indulge a question about R and the estimation of a linear regression with time-varying coefficients. The model I am trying to estimate is of the form: y(t) = beta(t) * x(t) + v(t) beta(t) = gamma * beta(t-1) + w(t) where gamma is a constant, v(t) and w(t) are Gaussian innovations, and where y(t) and x(t) are univariate time series that are known. I would like to estimate gamma and the variance of v(t) and w(t). I have tried using the following packages with no success: sspir, dse (specifically dse1) and dlm. In each case, any attempt to specify the above model meets with some sort of error. Hence, I have not been able to estimate the model. I am using "manufactured" data, i.e., I assume a value for gamma, beta(0), and values for the variances of v(t) and w(t), so I know what result I should attain. I would really appreciate any help on how to appropriately specify the above model in any of the packages I mentioned. Best regards, -Paul __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Running R non-interactively
Normally I can run an R script in batch mode with a command like this R CMD BATCH MyScript.R MyOutput & However I prefer to write another script containing something like R --no-restore --save --no-readline < $1 >$2 so that I could run the original script simply on the prompt as MyScript.R MyOutput & The second method is almost the same as the R CMD BATCH method except MyOutput does not contain the output from the OS calls such as system (). So what option(s) should add in the second approach to make it identical to R CMD BATCH? Thanks, Gang __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
"tom soyer" <[EMAIL PROTECTED]> writes: > (1) how do I encapsulate the generics? i.e., if a class has 100 methods, > then does it mean 100 generics would be dumped in the global environment? > Or, is it possible to define a local environment and restrict the generics > from one class to a particular environment? But then how do you call the > generics from a special environment? Also, is it possible to inherit classes > across different environment? I think the answer is: you can't. There is no sensible way to assign multi-methods to a particular class. So you have to have some sort of database of methods and signatures that gets consulted by the dispatcher. How you do a sensible IDE with this setup is beyond me. This is my biggest gripe with S4 methods: there doesn't seem to be any good way to browse the environment and discover whats already in there. S3 methods are much easier to follow. You can do multiple dispatch with S3 methods, but hardly anyone ever does. My view is that multiple dispatch is not worth the complexity it adds to a language. > (2) it seems that an R specific IDE would improve productivity dramatically > (maybe even necessary?) with respect to oop. Is there such an IDE and does > it work for oop? I recall a group (in Germany?) was working on it but I > can't remember where I read about it. -- Jeff __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
Thanks Gabor. I guess true oo encapsulation is not possible in R.
It seems that there is an IDE for S+ in Eclipse...
On 2/6/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
>
> On Feb 6, 2008 9:45 AM, tom soyer <[EMAIL PROTECTED]> wrote:
> > Thanks Gabor for illustrating the basics oop in R using S3. Maybe I
> didn't
> > have the right documents, but you example taught me more about oop in R
> than
> > everything else I read combined! Thanks for the tip on R.oo, I plan to
> check
> > it out later.
> >
> > I have a few followup questions...
> >
> > (1) how do I encapsulate the generics? i.e., if a class has 100 methods,
> > then does it mean 100 generics would be dumped in the global
> environment?
> > Or, is it possible to define a local environment and restrict the
> generics
> > from one class to a particular environment? But then how do you call the
> > generics from a special environment? Also, is it possible to inherit
> classes
> > across different environment?
>
> Both ofthe following return 3. If that is not what you are asking
> then I suggest you experiment with a few small examples of
> this nature:
>
> f <- function() {
>F <- function(x) UseMethod("F")
>F.default <- function(x) x
>F(3)
> }
> F.default <- function(x) NULL
> f()
>
>
> F <- function(x) UseMethod("F")
> f <- function() {
>F.default <- function(x) x
>F(3)
> }
> F.default <- function(x) NULL
> f()
>
> >
> > (2) it seems that an R specific IDE would improve productivity
> dramatically
> > (maybe even necessary?) with respect to oop. Is there such an IDE and
> does
> > it work for oop? I recall a group (in Germany?) was working on it but I
> > can't remember where I read about it.
> >
> > Thanks!
> >
> >
> > On 2/5/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
> > > This illustration uses S3. Note that functions do not modify their
> > arguments
> > > so to modify an object we have to pass it to the method and then pass
> the
> > > object back. There is also another system called S4 which involves
> typing
> > > of arguments and there are packages proto and R.oo which provide
> different
> > > OO models.
> > >
> > >
> > > # define constructors for bicycle and mountainBike classes
> > > Bicycle <- function(cadence, gear, speed) structure(list(cadence =
> > > cadence, gear = gear, speed = speed), class = "bicycle")
> > > MountainBike <- function(cadence, gear, speed, seatHeight) {
> > > x <- Bicycle(cadence, gear, speed)
> > > x$seatHeight <- seatHeight
> > > class(x) <- c(class(x), "mountainBike")
> > > x
> > > }
> > >
> > > # define generic setCadence and then methods for each class
> > >
> > > setCadence <- function(x, cadence) UseMethod("setCadence")
> > > setCadence.bicycle <- function(x, cadence) { x$cadence <- cadence; x }
> > >
> > > # mountBike's setCadence method overrides bicycle's setCadence method
> > > setCadence.mountBike <- function(x, cadence) { x$cadence <- cadence +
> 1; x
> > }
> > >
> > > # list the setCadence methods avialable
> > > methods(setCadence)
> > >
> > > # define a generic applyBrake and a "bicycle" method
> > > # mountainBike will inherit the bicycle method by default
> > > applyBrake <- function(x, decrement) UseMethod("applyBrake")
> > > applyBrake.bicycle <- function(x, decrement) { x$speed <- x$speed -
> > decrement }
> > >
> > > # list the applyBrake methods available
> > > methods(applyBrake)
> > >
> > > b <- Bicycle(1, 2, 3)
> > > m <- MountainBike(4, 5, 6, 7)
> > > m <- applyBrake(m, 1)
> > >
> > >
> > > On Feb 5, 2008 8:21 AM, tom soyer <[EMAIL PROTECTED]> wrote:
> > > > Hi,
> > > >
> > > > I read section 5, oop, of the R lang doc, and I am still not sure I
> > > > understand how to build a class in R for oop. I thought that since I
> > > > understand the oop syntex of Java and VB, I am wondering if the R
> > programmig
> > > > experts could help me out by comparing and contrasting the oop
> syntex in
> > R
> > > > with that of Java. For example, the basic class structure in Java is
> > like
> > > > this:
> > > >
> > > > public class Bicycle {
> > > >
> > > >// *the Bicycle class has three fields*
> > > >public int cadence;
> > > >public int gear;
> > > >public int speed;
> > > >
> > > >// *the Bicycle class has one constructor*
> > > >public Bicycle(int startCadence, int startSpeed, int startGear) {
> > > >gear = startGear;
> > > >cadence = startCadence;
> > > >speed = startSpeed;
> > > >}
> > > >
> > > >// *the Bicycle class has four methods*
> > > >public void setCadence(int newValue) {
> > > >cadence = newValue;
> > > >}
> > > >
> > > >public void setGear(int newValue) {
> > > >gear = newValue;
> > > >}
> > > >
> > > >public void applyBrake(int decrement) {
> > > >speed -= decrement;
> > > >}
> > > >
> > > >public void speedUp(int increment) {
> > > >speed += increment;
> > > >}
> > > >
> > > > }
> > > >
> > > > Could one of the R expe
[R] Discriminant function analysis
Hello R-Cracks, I am using R 2.6.1 on a PowerBook G4. I would like to perform a discriminant function analysis. I found lda in MASS but as far as I understood, is it only working with explanatory variables of the class factor. My dataset contains variables of the classes factor and numeric. Is there another function that is able to handle this? Thank you all in advance. Greetings Birgit Birgit Lemcke Institut für Systematische Botanik Zollikerstrasse 107 CH-8008 Zürich Switzerland Ph: +41 (0)44 634 8351 [EMAIL PROTECTED] 175 Jahre UZH «staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.» MNF-Jubiläumsevent für gross und klein. 19. April 2008, 10.00 Uhr bis 02.00 Uhr Campus Irchel, Winterthurerstrasse 190, 8057 Zürich Weitere Informationen www.175jahre.uzh.ch __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Multivariate Maximum Likelihood Estimation
It seems like you didn't look at the examples in the helpfiles. See ?gls and ?corAR1. ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 [EMAIL PROTECTED] www.inbo.be Do not put your faith in what statistics say until you have carefully considered what they do not say. ~William W. Watt A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions. ~M.J.Moroney -Oorspronkelijk bericht- Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Konrad BLOCHER Verzonden: woensdag 6 februari 2008 16:42 Aan: r-help@r-project.org Onderwerp: Re: [R] Multivariate Maximum Likelihood Estimation OK I got gls running but this is the error message that I got: > gls_results <- gls(LnWRPK ~ LnWGDP+LnWYIELD,correlation = corAR1) Error in switch(mode(x), "NULL" = structure(NULL, class = "formula"), : invalid formula Google didn't give any results unfortunately. Help! :) Thanks, KB > Have you tried gls()? > > > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > [EMAIL PROTECTED] > www.inbo.be > > Do not put your faith in what statistics say until you have carefully considered what they do not say. ~William W. Watt > A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions. ~M.J.Moroney > > -Oorspronkelijk bericht- > Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Konrad BLOCHER > Verzonden: woensdag 6 februari 2008 12:12 > Aan: r-help@r-project.org > Onderwerp: [R] Multivariate Maximum Likelihood Estimation > > Hi, > > I am trying to perform Maximum Likelihood estimation of a Multivariate model (2 independent variables + intercept) with autocorrelated errors of > 1st order (ar(1)). > > Does R have a function for that? I could only find an univariate option (ar.mle function) and when writing my own I find that it is pretty memory-consuming (and sometimes wrong) so there must be a better way. > > Thanks, > > KB > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] unload & reload a (new version of a) package
i returned to this problem and found that the solution was a disarmingly
straight-forward oversight on my part: 'detach' requires the version
number of the library to be specified!
thus, if you install packages '--with-package-versions' switched on,
and if you load the version of choice in an R session with:
> library(foo, version="1.0")
then you must 'detach' it in the same R session using
> detach(foo, version="1.0")
in the *same* R session you can load another version:
> library(foo, version="1.2")
and happily detach it with
> detach(foo, version="1.2")
and then go back to version 1.0 again (all in the same R session):
> library(foo, version="1.0")
thus obviating the behavior that i had previously reported.
-Original Message-
From: Harte, Thomas P
Sent: Tuesday, January 15, 2008 10:47 AM
To: r-help@r-project.org
Subject: RE: [R] unload & reload a (new version of a) package
update: this phenomenon disappears if i do a straight install *without*
package versioning, i.e.
C:\packages>c:\R\R-2.6.1\bin\R CMD BUILD foo_1.0
[creates foo_1.0.tar.gz]
C:\packages>c:\R\R-2.6.1\bin\R CMD INSTALL -l c:/library foo_1.0.tar.gz
i can update the package, re-build and re-install and load it into the
existing R session with a call to 'library(foo, lib.loc="c:/library")'
when i posted, i had been doing things *with versioning* switched on:
C:\packages>c:\R\R-2.6.1\bin\R CMD BUILD foo_1.0
[creates foo_1.0.tar.gz]
C:\packages>c:\R\R-2.6.1\bin\R CMD INSTALL --with-package-versions -l
c:/library foo_1.0.tar.gz
and loading it into the existing R session with 'library(foo,
lib.loc="c:/library", version="1.0")'.
so the problem seemes to exist if i install a newer version of the
package this way, thereby clobbering the old version foo_1.0 in the
process. however, if I copy the source tree for foo_1.0 and make a
*completely new version* foo_1.1, say, and install
--with-package-versions:
C:\packages>c:\R\R-2.6.1\bin\R CMD BUILD foo_1.1
C:\packages>c:\R\R-2.6.1\bin\R CMD INSTALL --with-package-versions -l
c:/library foo_1.1.zip
library(foo, lib.loc="c:/library", version="1.1")
then i can successfully load version 1.1
something is possibly wrong somewhere with versioning, or with my
package. either way, i can live without versioning switched on and just
clobber versions of the library foo with the updated package foo.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Harte, Thomas P
Sent: Monday, January 14, 2008 6:49 PM
To: r-help@r-project.org
Subject: [R] unload & reload a (new version of a) package
i'm putting the final touches on a package that i'm developing and i
noticed that if i detach the package, and then re-build & re-install it
(using R
CMD)
then I can't get the newer version of the package to load in the
existing R session (i have to close it out and start a new session, then
the newer
version of the package is loaded).
looking through the source of 'detach' i see :
.Call("R_lazyLoadDBflush", paste(libpath, "/R/", pkgname,
".rdb", sep = ""), PACKAGE = "base")
is there some absolute way similar to the above to flush the package db
and ensure that a newer version of the package can be loaded into the
existing R session? detach calls .Last.lib and seems to go through the
motions of purging the loaded package; why, then, is the package still
lurking around in the existing R session?
it's not a big deal; it's only a minor pain having to re-start an R
session. i'm more interesting in why this is happening.
cheers,
thomas.
This message, including any attachments, contains\ confi...{{dropped:26}}
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Re: [R] Levelplot of percentages always using 0 to 100 in the color scheme
On 2/5/08, Kelvin <[EMAIL PROTECTED]> wrote:
> I am trying to create levelplot's of cpu usage for systems.
> print(levelplot(util.mean ~ x.hour * x.day, colorkey=T, cut=20,
> scales=list(x=list(at=seq(0,96,length=25),
> labels=ifelse(seq(0,24) %% 4 == 0, seq(0,24), ''))), # add
> tick marks at the hour
> main="CPU Utilization During November on idnprod",
>
> col.regions=colorRampPalette(c('white','green','yellow','red'))(101), #
> 101 colors
> xlab="Hours (15 minute intervals)", ylab="Day of the Month")
> )
> util.mean has the utilizations by timestamps
> If the values in util.mean are only 10-50, the plot codes 10 as white
> and low and 50 as red and high.
> What I would desire is the 0 is always the low and white and 100 always
> the high and red.
Specify a suitable 'at' argument; e.g.,
at = seq(0, 100, length = 51)
-Deepayan
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Re: [R] advice requested re: building "good" system (R, SQL db) for handling large datasets
Richard Pearson wrote on 02/06/2008 06:25 AM: > Hi Thomas [...] > With databases, one issue that might be relevant is whether you want to > store data in tables (e.g. one table to store one data.frame) that can > subsequently be manipulated in the DB, or to store R objects as R > objects (e.g. as BLOBs). My situation is likely to be the later case, > and one of my concerns is that many DBs have an upper limit of 2GB on > BLOBs, and I might potentially have objects that are larger than this. [...] I'd be curious as to why you'd want to store and retrieve R objects from a BLOB column in a table. I've often thought about this, but unfortunately neither the DBI package nor the RODBC package support this. Jeff -- http://biostat.mc.vanderbilt.edu/JeffreyHorner __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] wilderSum
Shubha,
The calculation is:
wilderSum[1] <- x[1]
for(i in 2:NROW(x)) {
wilderSum[i] <- x[i] + wilderSum[i-1] * (n-1)/n
}
Where 'x' is the price series and 'n' is the number of periods.
You can see the calculations for all functions in TTR's source code,
which is on CRAN and r-forge
(http://r-forge.r-project.org/projects/ttr/).
Please feel free to contact me directly regarding questions about TTR.
Best,
Josh
On Feb 6, 2008 8:22 AM, Shubha Vishwanath Karanth
<[EMAIL PROTECTED]> wrote:
>
> Hi,
>
> Can somebody tell me the formula for "?wilderSum" in TTR package? I mean how
> are these calculated?
>
> BR, Shubha
>
> Shubha Karanth | Amba Research
>
> Ph +91 80 3980 8031 | Mob +91 94 4886 4510
>
> Bangalore • Colombo • London • New York • San José • Singapore •
> www.ambaresearch.com
>
> This e-mail may contain confidential and/or privileged information. If you
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Re: [R] 3d scatterplot with error bars
Christopher Chizinski wrote:
> Is there anyway to produce a 3D scatterplot with error bars in the x,y,z
> directions? I have searched around and know of scatterplot3d but did
> not see any way to put error bars on the points. Any ideas?
Yes, type
vignette("s3d", package="scatterplot3d")
and see page 22.
Uwe Ligges
> __
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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Re: [R] advice requested re: building "good" system (R, SQL db) for handling large datasets
On Wed, Feb 06, 2008 at 02:34:52PM +0200, Rainer M Krug wrote: > R objects in blobs - I never thought about that. Could you elaborate on how > to do something like that (I am using RMySQL)? Look at help(serialize) -- any R object can be turned into a suitable representation, either binary (more efficient) or ascii (possibly 'safer'). Store that, retrieve it later, reconstruct the object and be merry :) > tmpDf <- data.frame(a=1:10, b=LETTERS[1:10], c=rnorm(10)) > serDf <- serialize(tmpDf, NULL, ascii=TRUE) > rm(tmpDf) > head(unserialize(serDf)) a b c 1 1 A -0.6945820 2 2 B -0.2960084 3 3 C -0.2514302 4 4 D -0.7318635 5 5 E -0.1698489 6 6 F 0.4331521 > Dirk -- Three out of two people have difficulties with fractions. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Inconsistent lattice scales$x$at, label behaviour for POSIXct
On 2/6/08, Alex Brown <[EMAIL PROTECTED]> wrote:
> Here's a related problem that works for numeric but not for POSIXct
>
> I am seeing it where a panel has no at labels, but others do.
>
> This simple example only has one panel with no at labels.
>
> > baseval = 0;
> > xyplot(1:10 ~ (baseval + c(1:10)), scales=list(x=list
> + (at=list(c()), labels=list(c()), relation="free")), type="l")
>
> (works)
>
> baseval = as.POSIXct("2007-01-01");
> > xyplot(1:10 ~ (baseval + c(1:10)), scales=list(x=list
> + (at=list(c()), labels=list(c()), relation="free")), type="l")
> Error in as.POSIXct.default(at) :
> do not know how to convert 'at' to class "POSIXlt"
There may be a better long-term solution, but does this work for now?:
> xyplot(1:10 ~ (baseval + c(1:10)), scales=list(x=list
+ (at=list(baseval + c()), labels=list(c()), relation="free")), type="l")
-Deepayan
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Re: [R] 3d scatterplot with error bars
> Is there anyway to produce a 3D scatterplot with error bars in the x,y,z > directions? I have searched around and know of scatterplot3d but did > not see any way to put error bars on the points. Any ideas? It may be possible, but do you think that's the best solution for your problem? Given that any 3d plot must be projected into two dimensions, how on earth will people be able to compare the relative magnitude in each direction or between points? One could imagine drawing error ellispoids (since you might as well include covariance information as well) but I would imagine that the tight connection between the view of the data and the two-D projection of the ellipsoid (representing a particular linear combination of the x, y and z errors) would make it very difficult to see what's going on. Not to mention the difficulties with near points obscuring far points, etc etc. Hadley -- http://had.co.nz/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] 3d scatterplot with error bars
> Yes, type
>
> vignette("s3d", package="scatterplot3d")
>
> and see page 22.
which of course won't work unless you have scatterplot3d installed,
but I wonder if vignette() could be modified to try to find the
vignette on the web if the package isn't installed. It would make it
a little easy to read about a package before installing it.
Hadley
--
http://had.co.nz/
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Re: [R] Multivariate Maximum Likelihood Estimation
Thanks, I managed to run gls, but my problem isn't solved :) 1. I do not know the autocorrelation between errors and its estimates change for different methods. Therefore I wasn't including it in the corAR1 function. 2. GLS yields counteraintuitive results with one of the variables (its sign) and I need to make sure that it is either only the case for Least Squares, or for the data (disregarding the influence of different estimation techniques) - thus a need for multivariate MLE. Cheers, KB > It seems like you didn't look at the examples in the helpfiles. See ?gls > and ?corAR1. > > > > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature > and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, > methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > [EMAIL PROTECTED] > www.inbo.be > > Do not put your faith in what statistics say until you have carefully > considered what they do not say. ~William W. Watt > A statistical analysis, properly conducted, is a delicate dissection of > uncertainties, a surgery of suppositions. ~M.J.Moroney > > -Oorspronkelijk bericht- > Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > Namens Konrad BLOCHER > Verzonden: woensdag 6 februari 2008 16:42 > Aan: r-help@r-project.org > Onderwerp: Re: [R] Multivariate Maximum Likelihood Estimation > > OK I got gls running but this is the error message that I got: > >> gls_results <- gls(LnWRPK ~ LnWGDP+LnWYIELD,correlation = corAR1) > > Error in switch(mode(x), "NULL" = structure(NULL, class = "formula"), : > invalid formula > > Google didn't give any results unfortunately. > > Help! :) > > Thanks, > > KB > >> Have you tried gls()? >> >> >> > > >> ir. Thierry Onkelinx >> Instituut voor natuur- en bosonderzoek / Research Institute for Nature > and Forest >> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, > methodology and quality assurance >> Gaverstraat 4 >> 9500 Geraardsbergen >> Belgium >> tel. + 32 54/436 185 >> [EMAIL PROTECTED] >> www.inbo.be >> >> Do not put your faith in what statistics say until you have carefully > considered what they do not say. ~William W. Watt >> A statistical analysis, properly conducted, is a delicate dissection > of > uncertainties, a surgery of suppositions. ~M.J.Moroney >> >> -Oorspronkelijk bericht- >> Van: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] > Namens Konrad BLOCHER >> Verzonden: woensdag 6 februari 2008 12:12 >> Aan: r-help@r-project.org >> Onderwerp: [R] Multivariate Maximum Likelihood Estimation >> >> Hi, >> >> I am trying to perform Maximum Likelihood estimation of a Multivariate > model (2 independent variables + intercept) with autocorrelated errors > of >> 1st order (ar(1)). >> >> Does R have a function for that? I could only find an univariate > option > (ar.mle function) and when writing my own I find that it is pretty > memory-consuming (and sometimes wrong) so there must be a better way. >> >> Thanks, >> >> KB >> >> __ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
On Feb 6, 2008 10:13 AM, tom soyer <[EMAIL PROTECTED]> wrote: > Thanks Gabor. I guess true oo encapsulation is not possible in R. Before making such a claim, I would encourage you to actually learn what oo means. A couple of good readings are: Structure and Interpretation of Computer Programs. http://mitpress.mit.edu/sicp/ Concepts, Techniques, and Models of Computer Programming. http://www.info.ucl.ac.be/~pvr/book.html Java style (message passing) oo is not the entirety of oo-based programming! Hadley -- http://had.co.nz/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] ci.pd() (Epi) and Newcombe method
Greetings!
I suspect that there is an error in the code for the
function ci.pd() in the Epi package.
This function is for computing confidence intervals
for a difference of proportions between two independent
groups of 0/1 responses, and implements the Newcombe
("Nc") method and the Agrasti-Caffo "AC" method.
I think there is an error in the computation for the
Newcombe method.
Specifically, where the code says
# Put the data in the right form
x1 <- aa; n1 <- aa+cc; p1 <- x1/n1
x2 <- bb; n2 <- bb+dd; p2 <- x2/n2
pd <- x1/n1 - x2/n2
z <- qnorm(1-alpha/2)
zz <- qchisq(1-alpha/2,1)
I believe zz (which is used in the Newcombe method,
while z is used for Agresti-Caffo) should be
zz <- qchisq(1-alpha,1)
(though I think they could just as well have written
xx <- z^2), since z^2 seems to be what they want for the
Newcombe method, and qnorm(1-alpha/2)^2 = qchisq(1-alpha,1)
This was noticed as a result of comparing results from
ci.pd() with results from the RDCI module in STATA (run
by someone else, since I don't have access to STATA).
With the original code in ci.pd(), the Newcombe results
were different between ci.pd() and STATA. After making
the above change, they agreed.
I would be most grateful if anyone who has also been
down this path could confirm whether I am correct.
Since I don't have access to Newcombe's original
paper at the moment either, I am not able to check
the code against his own description of the method!
With thanks,
Ted.
E-Mail: (Ted Harding) <[EMAIL PROTECTED]>
Fax-to-email: +44 (0)870 094 0861
Date: 06-Feb-08 Time: 16:58:19
-- XFMail --
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[R] adding original axis for x and y to a plot
Hi. I have a AFTD plot. I want to add a original axis for x and y. I did "help(plot)". But I did not see an option for that. I need help. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] ci.pd() (Epi) and Newcombe method
(Ted Harding) wrote:
> Greetings!
>
> I suspect that there is an error in the code for the
> function ci.pd() in the Epi package.
>
Any particular reason not to include the maintainer among the
recipients?? Not sure whether Bendix is subscribed.
-p
> This function is for computing confidence intervals
> for a difference of proportions between two independent
> groups of 0/1 responses, and implements the Newcombe
> ("Nc") method and the Agrasti-Caffo "AC" method.
>
> I think there is an error in the computation for the
> Newcombe method.
>
> Specifically, where the code says
>
> # Put the data in the right form
> x1 <- aa; n1 <- aa+cc; p1 <- x1/n1
> x2 <- bb; n2 <- bb+dd; p2 <- x2/n2
> pd <- x1/n1 - x2/n2
> z <- qnorm(1-alpha/2)
> zz <- qchisq(1-alpha/2,1)
>
> I believe zz (which is used in the Newcombe method,
> while z is used for Agresti-Caffo) should be
>
> zz <- qchisq(1-alpha,1)
>
> (though I think they could just as well have written
> xx <- z^2), since z^2 seems to be what they want for the
> Newcombe method, and qnorm(1-alpha/2)^2 = qchisq(1-alpha,1)
>
> This was noticed as a result of comparing results from
> ci.pd() with results from the RDCI module in STATA (run
> by someone else, since I don't have access to STATA).
> With the original code in ci.pd(), the Newcombe results
> were different between ci.pd() and STATA. After making
> the above change, they agreed.
>
> I would be most grateful if anyone who has also been
> down this path could confirm whether I am correct.
> Since I don't have access to Newcombe's original
> paper at the moment either, I am not able to check
> the code against his own description of the method!
>
> With thanks,
> Ted.
>
>
> E-Mail: (Ted Harding) <[EMAIL PROTECTED]>
> Fax-to-email: +44 (0)870 094 0861
> Date: 06-Feb-08 Time: 16:58:19
> -- XFMail --
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
Thanks Hardley. I see what you mean. You are right, I am not an expert in oop AND I don't really know how R oo works, so certainly I shouldn't be making any sweeping statement. I was just thinking about the issue of local vs. global, i.e. changes intended for the local environment shouldn't affect the global environment. That was all I meant. On 2/6/08, hadley wickham <[EMAIL PROTECTED]> wrote: > > On Feb 6, 2008 10:13 AM, tom soyer <[EMAIL PROTECTED]> wrote: > > Thanks Gabor. I guess true oo encapsulation is not possible in R. > > Before making such a claim, I would encourage you to actually learn > what oo means. A couple of good readings are: > > Structure and Interpretation of Computer Programs. > http://mitpress.mit.edu/sicp/ > > Concepts, Techniques, and Models of Computer Programming. > http://www.info.ucl.ac.be/~pvr/book.html > > Java style (message passing) oo is not the entirety of oo-based > programming! > > Hadley > > -- > http://had.co.nz/ > -- Tom [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Maximum number of variables allowed in a multiple linearregression model
Bert Gunter wrote:
> I strongly suggest you collaborate with a local statistician. I can think of
> no circumstance where multiple regression on "hundreds of thousands of
> variables" is anything more than a fancy random number generator.
That sounds like a challenge! What is the largest regression problem (in
terms of numbers of variables) that people have encountered where it made
sense to do some sort of linear regression (and gave useful results)?
(Including multilevel and Bayesian techniques.)
However, the original poster did say "hundreds to thousands", which is
smaller than "hundreds of thousands". When I try a regression problem with
3,000 coefficients in R running under Windows XP 64 bit with 8Gb of memory
on the machine and the /3Gb option active (i.e., R can get up to 3Gb), R
2.6.1 runs out of memory (apparently trying to duplicate the model matrix):
R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
> m <- 3000
> n <- m * 10
> x <- matrix(rnorm(n*m), ncol=m, nrow=n,
dimnames=list(paste("C",1:n,sep=""), paste("X",1:m,sep="")))
> dim(x)
[1] 3 3000
> k <- sample(m, 10)
> y <- rowSums(x[,k]) + 10 * rnorm(n)
> fit <- lm.fit(y=y, x=x)
Error: cannot allocate vector of size 686.6 Mb
> object.size(x)/2^20
[1] 687.7787
> memory.size()
[1] -2022.552
>
and the Windows process monitor shows the peak memory usage for Rgui.exe at
2,137,923K. But in a 64 bit version of R, I would be surprised if it was
not possible to run this (given sufficient memory).
However, R easily handles a slightly smaller problem:
> m <- 1000 # of variables
> n <- m * 10 # of rows
> k <- sample(m, 10)
> x <- matrix(rnorm(n*m), ncol=m, nrow=n,
dimnames=list(paste("C",1:n,sep=""), paste("X",1:m,sep="")))
> y <- rowSums(x[,k]) + 10 * rnorm(n)
> fit <- lm.fit(y=y, x=x)
> # distribution of coefs that should be one vs zero
> round(rbind(one=quantile(fit$coefficients[k]),
zero=quantile(fit$coefficients[-k])), digits=2)
0% 25% 50% 75% 100%
one 0.94 0.98 1.04 1.10 1.18
zero -0.30 -0.08 -0.01 0.06 0.29
>
To echo Bert Gunter's cautions, one must be careful doing ordinary linear
regression with large numbers of coefficients. It does seem a little
unlikely that there is sufficient data to get useful estimates of three
thousand coefficients using linear regression in data managed in Excel
(though I guess it could be possible using Excel 12.0, which can handle up
to 1 million rows - recent versions prior to 2008 could handle on 64K rows
- see http://en.wikipedia.org/wiki/Microsoft_Excel#Versions ). So, the
suggestion to consult a local statistician is good advice - there may be
other more suitable approaches, and if some form of linear regression is an
appropriate approach, there are things to do to gain confidence that the
results of the linear regression convey useful information.
-- Tony Plate
>
> -- Bert Gunter
> Genentech Nonclinical Statistics
>
> -Original Message-
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
> Behalf Of Michelle Chu
> Sent: Tuesday, February 05, 2008 9:00 AM
> To: R-help@r-project.org
> Subject: [R] Maximum number of variables allowed in a multiple
> linearregression model
>
> Hi,
>
> I appreciate it if someone can confirm the maximum number of variables
> allowed in a multiple linear regression model. Currently, I am looking for
> a software with the capacity of handling approximately 3,000 variables. I
> am using Excel to process the results. Any information for processing a
> matrix from Excel with hundreds to thousands of variables will helpful.
>
> Best Regards,
> Michelle
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ci.pd() (Epi) and Newcombe method
On 06-Feb-08 17:09:59, Peter Dalgaard wrote:
> (Ted Harding) wrote:
>> Greetings!
>>
>> I suspect that there is an error in the code for the
>> function ci.pd() in the Epi package.
>>
> Any particular reason not to include the maintainer among the
> recipients??
Oversight, and haste! Thank you for copying your reply
(with my original message) to him. And apologies to Bendix.
Ted.
> Not sure whether Bendix is subscribed.
>
> -p
>
>> This function is for computing confidence intervals
>> for a difference of proportions between two independent
>> groups of 0/1 responses, and implements the Newcombe
>> ("Nc") method and the Agrasti-Caffo "AC" method.
>>
>> I think there is an error in the computation for the
>> Newcombe method.
>>
>> Specifically, where the code says
>>
>> # Put the data in the right form
>> x1 <- aa; n1 <- aa+cc; p1 <- x1/n1
>> x2 <- bb; n2 <- bb+dd; p2 <- x2/n2
>> pd <- x1/n1 - x2/n2
>> z <- qnorm(1-alpha/2)
>> zz <- qchisq(1-alpha/2,1)
>>
>> I believe zz (which is used in the Newcombe method,
>> while z is used for Agresti-Caffo) should be
>>
>> zz <- qchisq(1-alpha,1)
>>
>> (though I think they could just as well have written
>> xx <- z^2), since z^2 seems to be what they want for the
>> Newcombe method, and qnorm(1-alpha/2)^2 = qchisq(1-alpha,1)
>>
>> This was noticed as a result of comparing results from
>> ci.pd() with results from the RDCI module in STATA (run
>> by someone else, since I don't have access to STATA).
>> With the original code in ci.pd(), the Newcombe results
>> were different between ci.pd() and STATA. After making
>> the above change, they agreed.
>>
>> I would be most grateful if anyone who has also been
>> down this path could confirm whether I am correct.
>> Since I don't have access to Newcombe's original
>> paper at the moment either, I am not able to check
>> the code against his own description of the method!
>>
>> With thanks,
>> Ted.
>>
>>
>> E-Mail: (Ted Harding) <[EMAIL PROTECTED]>
>> Fax-to-email: +44 (0)870 094 0861
>> Date: 06-Feb-08 Time: 16:58:19
>> -- XFMail --
>>
>> __
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
> --
>O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B
> c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
> (*) \(*) -- University of Copenhagen Denmark Ph: (+45)
> 35327918
> ~~ - ([EMAIL PROTECTED]) FAX: (+45)
> 35327907
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
E-Mail: (Ted Harding) <[EMAIL PROTECTED]>
Fax-to-email: +44 (0)870 094 0861
Date: 06-Feb-08 Time: 17:29:34
-- XFMail --
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] inserting text lines in a dat frame
Hi Jim
yes, this exactly want I want. However, I need one more step to get
rid of the first column so that the final file looks like this:
browser
position
chr1:1-1
browser
hide
all
track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full
variableStep
chrom=chr1
span=1
11255 55
11320
29
11400
45
track
type=wiggle_0
name=sample
description=chr2_sample
visibility=full
variableStep
chrom=chr2
span=1
21680
35
21750
84
21820
29
track
type=wiggle_0
name=sample
description=chr3_sample
visibility=full
variableStep
chrom=chr3
span=1
32100
29
32170
45
32240
45
Thank you very much
- Original Message
From: jim holtman <[EMAIL PROTECTED]>
To: joseph <[EMAIL PROTECTED]>
Cc: r-help@r-project.org
Sent: Wednesday, February 6, 2008 2:37:38 AM
Subject: Re: inserting text lines in a dat frame
Try
this
and
see
if
it
is
what
you
want:
x
<-
read.table(textConnection("
V1
V2
V3
1
chr1
11255
55
2
chr1
11320
29
3
chr1
11400
45
4
chr2
21680
35
5
chr2
21750
84
6
chr2
21820
29
7
chr2
31890
46
8
chr3
32100
29
9
chr3
52380
29
10
chr3
66450
46"
),
header=TRUE)
cat("browser
position
chr1:1-1\nrowser
hide
all\n",
file='tempxx.txt')
result
<-
lapply(split(x,
x$V1),
function(.chro){
cat(sprintf("track
type=wiggle_0
name=sample
description=%s_sample
visibility=full\nvariableStep
chrom=%s
span=1\n",
as.character(.chro$V1[1]),
as.character(.chro$V1[1])),
file="tempxx.txt",
append=TRUE)
write.table(.chro,
sep="\t",
file="tempxx.txt",
append=TRUE,
col.names=FALSE,
row.names=FALSE)
})
On
Feb
5,
2008
11:22
PM,
joseph
<[EMAIL PROTECTED]>
wrote:
>
>
>
>
>
>
Hi
Jim
>
I
am
trying
to
prepare
a
bed
file
to
load
as
accustom
track
on
the
UCSC
>
genome
browser.
>
I
have
a
data
frame
that
looks
like
the
one
below.
>
>
x
>
V1
V2
V3
>
1
chr1
11255
55
>
2
chr1
11320
29
>
3
chr1
11400
45
>
4
chr2
21680
35
>
5
chr2
21750
84
>
6
chr2
21820
29
>
7
chr2
31890
46
>
8
chr3
32100
29
>
9
chr3
52380
>
29
>
10
chr3
66450
46
>
I
would
like
to
insert
the
following
4
lines
at
the
beginning:
>
browser
position
chr1:1-1
>
browser
hide
all
>
track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full
>
variableStep
chrom=chr1
span=1
>
and
then
insert
2
lines
before
each
chromosome:
>
track
type=wiggle_0
name=sample
description=chr2_sample
visibility=full
>
vriableStep
chrom=chr2
span=1
>
The
final
result
should
be
tab
delimited
file
that
looks
like
this:
>
browser
position
chr1:1-1
>
browser
hide
all
>
track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full
>
variableStep
chrom=chr1
span=1
>
chr1
11255
55
>
chr1
11320
29
>
chr1
11400
45
>
track
type=wiggle_0
name=sample
description=chr2_sample
visibility=full
>
variableStep
chrom=chr2
span=1
>
chr2
21680
35
>
chr2
21750
84
>
chr2
21820
29
>
track
type=wiggle_0
name=sample
description=chr3_sample
visibility=full
>
variableStep
chrom=chr3
>
span=1
>
chr3
32100
29
>
chr3
32170
45
>
chr3
32240
45
>
Any
kind
of
help
or
guidance
will
be
much
appreciated.
>
Joseph
>
>
>
Be
a
better
friend,
newshound,
and
know-it-all
with
Mobile.
Try
it
>
now.
--
Jim
Holtman
Cincinnati,
OH
+1
513
646
9390
What
is
the
problem
you
are
trying
to
solve?
Be a better friend, newshound, and
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] kruskal's MONANOVA algorithm
I am trying to obtain the Kruskal (1964) secondary least-squares monotonic transformation of a rank variable given 4 categorical variables in order to obtain optimal transformation for regression. The academic problem assigned is to compare R, SPSS (Conjoint Analysis), and SAS' proc transreg in speed and accuracy. Currently, SAS and SPSS are giving similar results, but R's are quite different. There is something I am misunderstanding about acepackage and/or isoMDS. The data looks like this: Brand Price Life Hazard Rank 1 Goodstone $69.99 60,000Yes3 2 Goodstone $69.99 70,000 No2 ... 7 Pirogi $69.99 50,000 No7 8 Pirogi $69.99 70,000 No1 9 Pirogi $74.99 50,000Yes8 The ace and avas functions transform the y values into very small values of rank, like this: $ty [1] -1.3552125 -1.6732919 0.8859707 and hence the estimates are quite different. The R-squared is .93 while SAS and SPSS give .99. The isoMDS from MASS package gives weird results when i choose k=4. Here is my acepackage code and isoMDS function: X <- cbind(Brand, Price, Life, Hazard) # independent variables Y <- Rank # response variable cate <- as.vector(c(1,2,3,4)) # categorical variables(columns) in X mycon <- avas(x=X, y=Y, cat=cate) mymatrix <- as.matrix((X) row.names(mymatrix) <- Rank Any help is well appreciated. Thanks. myc <- isoMDS(dist(mymatrix), k=?) [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
If you believe that certain changes intended only to affect the local environment nevertheless affect the global environment please give a code example. On Feb 6, 2008 12:11 PM, tom soyer <[EMAIL PROTECTED]> wrote: > Thanks Hardley. I see what you mean. You are right, I am not an expert in > oop AND I don't really know how R oo works, so certainly I shouldn't be > making any sweeping statement. I was just thinking about the issue of local > vs. global, i.e. changes intended for the local environment shouldn't affect > the global environment. That was all I meant. > > > On 2/6/08, hadley wickham <[EMAIL PROTECTED]> wrote: > > > > On Feb 6, 2008 10:13 AM, tom soyer <[EMAIL PROTECTED]> wrote: > > > Thanks Gabor. I guess true oo encapsulation is not possible in R. > > > > Before making such a claim, I would encourage you to actually learn > > what oo means. A couple of good readings are: > > > > Structure and Interpretation of Computer Programs. > > http://mitpress.mit.edu/sicp/ > > > > Concepts, Techniques, and Models of Computer Programming. > > http://www.info.ucl.ac.be/~pvr/book.html > > > > Java style (message passing) oo is not the entirety of oo-based > > programming! > > > > Hadley > > > > -- > > http://had.co.nz/ > > > > > > -- > Tom > >[[alternative HTML version deleted]] > > __ > > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] inserting text lines in a dat frame
thanks Richie. It woks perfectly.
- Original Message
From: "[EMAIL PROTECTED]" <[EMAIL PROTECTED]>
To: joseph <[EMAIL PROTECTED]>
Cc: r-help@r-project.org; [EMAIL PROTECTED]
Sent: Wednesday, February 6, 2008 2:22:16 AM
Subject: Re: [R] inserting text lines in a dat frame
>
I
am
trying
to
prepare
a
bed
file
to
load
as
accustom
track
on
the
>
UCSC
genome
browser.
>
I
have
a
data
frame
that
looks
like
the
one
below.
>
>
x
>
V1
V2
V3
>
1
chr1
11255
55
>
2
chr1
11320
29
>
3
chr1
11400
45
>
4
chr2
21680
35
>
5
chr2
21750
84
>
6
chr2
21820
29
>
7
chr2
31890
46
>
8
chr3
32100
29
>
9
chr3
52380
29
>
10
chr3
66450
46
>
I
would
like
to
insert
the
following
4
lines
at
the
beginning:
>
browser
position
chr1:1-1
>
browser
hide
all
>
track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full
>
variableStep
chrom=chr1
span=1
>
and
then
insert
2
lines
before
each
chromosome:
>
track
type=wiggle_0
name=sample
description=chr2_sample
visibility=full
>
vriableStep
chrom=chr2
span=1
>
The
final
result
should
be
tab
delimited
file
that
looks
like
this:
>
browser
position
chr1:1-1
>
browser
hide
all
>
track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full
>
variableStep
chrom=chr1
span=1
>
chr1
11255
55
>
chr1
11320
29
>
chr1
11400
45
>
track
type=wiggle_0
name=sample
description=chr2_sample
visibility=full
>
variableStep
chrom=chr2
span=1
>
chr2
21680
35
>
chr2
21750
84
>
chr2
21820
29
>
track
type=wiggle_0
name=sample
description=chr3_sample
visibility=full
>
variableStep
chrom=chr3
span=1
>
chr3
32100
29
>
chr3
32170
45
>
chr3
32240
45
#First
write
your
preamble
text
to
a
file
preamble
<-
c("browser
position
chr1:1-1",
"browser
hide
all",
"track
type=wiggle_0
name=sample
description=chr1_sample
visibility=full",
"variableStep
chrom=chr1
span=1")
write(preamble,
"myfile.txt")
#Now
split
your
data
frame
up
by
the
values
in
V1
x
<-
data.frame(V1=rep(c("chr1",
"chr2",
"chr3"),times=c(3,4,3)),
V2=c(11255,11320,11400,21680,21750,21820,21890,32100,52380,66450),V3=c(55,29,45,35,84,29,46,29,29,46))
spx
<-
split(x,
x$V1)
#Create
lines
of
text
to
go
before
each
piece
of
data
frame
lV1
<-
levels(x$V1)
maintext
<-
paste("track
type=wiggle_0
name=sample
description=",
lV1,
"_sample
visibility=full\nvariableStep
chrom=",
lV1,
"
span=1",
sep="")
#Use
a
loop
to
write
the
pieces
to
the
file
for(i
in
1:
nlevels(x$V1))
{
write(maintext[i],
"myfile.txt",
append=TRUE)
write.table(spx[[i]],
"myfile.txt",
append=TRUE,
sep="\t",
quote=FALSE,
col.names=FALSE,
row.names=FALSE)
}
Regards,
Richie.
Mathematical
Sciences
Unit
HSL
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[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] box.Cox.powers() warning
Dear Rlist, Using an example in box.cox.powers() help, I have the following warning message. example: library(car) >attach(Prestige) > box.cox.powers(income) Box-Cox Transformation to Normality Est.Power Std.Err. Wald(Power=0) Wald(Power=1) 0.1793 0.11081.6179 -7.4062 L.R. test, power = 0: 2.7103 df = 1 p = 0.0997 L.R. test, power = 1: 47.261 df = 1 p = 0 Warning message: In optimize(f = function(lambda) univ.neg.kernel.logL(x = X[, j], : NA/Inf replaced by maximum positive value I do not know the reason for such warning message. Can someone help me on this matter? Best regards, Clara Cordeiro > sessionInfo() R version 2.6.1 (2007-11-26) i386-pc-mingw32 locale: LC_COLLATE=Portuguese_Portugal.1252;LC_CTYPE=Portuguese_Portugal.1252;LC_MONETARY=Portuguese_Portugal.1252;LC_NUMERIC=C;LC_TIME=Portuguese_Portugal.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] nnet_7.2-38car_1.2-7 MASS_7.2-38FitAR_1.0 leaps_2.7 [6] lattice_0.17-2 loaded via a namespace (and not attached): [1] grid_2.6.1 tools_2.6.1 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
Gabor, maybe I am not understanding it right. I was thinking for example something like how a call to plot actually calls plot.zoo when zoo is loaded. And a specific call to plot.zoo would not work, etc. One would think that plot and plot.zoo are separate and that one could call the parent as well as the offsprings independently. But if this kind of setup is by design, than it's fine. Does that make sense? On 2/6/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > > If you believe that certain changes intended only to affect the local > environment nevertheless affect the global environment please give a > code example. > > On Feb 6, 2008 12:11 PM, tom soyer <[EMAIL PROTECTED]> wrote: > > Thanks Hardley. I see what you mean. You are right, I am not an expert > in > > oop AND I don't really know how R oo works, so certainly I shouldn't be > > making any sweeping statement. I was just thinking about the issue of > local > > vs. global, i.e. changes intended for the local environment shouldn't > affect > > the global environment. That was all I meant. > > > > > > On 2/6/08, hadley wickham <[EMAIL PROTECTED]> wrote: > > > > > > On Feb 6, 2008 10:13 AM, tom soyer <[EMAIL PROTECTED]> wrote: > > > > Thanks Gabor. I guess true oo encapsulation is not possible in R. > > > > > > Before making such a claim, I would encourage you to actually learn > > > what oo means. A couple of good readings are: > > > > > > Structure and Interpretation of Computer Programs. > > > http://mitpress.mit.edu/sicp/ > > > > > > Concepts, Techniques, and Models of Computer Programming. > > > http://www.info.ucl.ac.be/~pvr/book.html > > > > > > Java style (message passing) oo is not the entirety of oo-based > > > programming! > > > > > > Hadley > > > > > > -- > > > http://had.co.nz/ > > > > > > > > > > > -- > > Tom > > > >[[alternative HTML version deleted]] > > > > __ > > > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > -- Tom [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with oop in R - class structure and syntex
zoo has a NAMESPACE which restricts access to the internals of the package except for explicitly exported items. zoo exports plot.zoo as an S3 method so that the plot generic can find it. It is also possible to simply export a function not specifically as an S3 method in which case it will be visible more generally. For example see seq.dates in chron. seq.dates is a seq method but can be called directly too since it was exported directly. # plot.zoo exported as S3 method library(zoo) z <- zoo(1:10) plot(z) # plot.zoo has been exported as S3 method zoo:::plot.zoo(z) # same output - not recommended # plot.zoo(z) # won't work # seq.dates exported library(chron) x <- chron(1:10) seq(x[1], x[10]) seq.dates(x[1], x[10]) # direct access - same output If an object is not exported at all then it cannot be accessed (other than via ::: notation). The other type of package is one with no NAMESPACE. In that case everything in the package is visible. On Feb 6, 2008 1:16 PM, tom soyer <[EMAIL PROTECTED]> wrote: > Gabor, maybe I am not understanding it right. I was thinking for example > something like how a call to plot actually calls plot.zoo when zoo is > loaded. And a specific call to plot.zoo would not work, etc. One would think > that plot and plot.zoo are separate and that one could call the parent as > well as the offsprings independently. But if this kind of setup is by > design, than it's fine. Does that make sense? > > > On 2/6/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > > > If you believe that certain changes intended only to affect the local > > environment nevertheless affect the global environment please give a > > code example. > > > > On Feb 6, 2008 12:11 PM, tom soyer <[EMAIL PROTECTED]> wrote: > > > Thanks Hardley. I see what you mean. You are right, I am not an expert > in > > > oop AND I don't really know how R oo works, so certainly I shouldn't be > > > making any sweeping statement. I was just thinking about the issue of > local > > > vs. global, i.e. changes intended for the local environment shouldn't > affect > > > the global environment. That was all I meant. > > > > > > > > > On 2/6/08, hadley wickham <[EMAIL PROTECTED]> wrote: > > > > > > > > On Feb 6, 2008 10:13 AM, tom soyer <[EMAIL PROTECTED]> wrote: > > > > > Thanks Gabor. I guess true oo encapsulation is not possible in R. > > > > > > > > Before making such a claim, I would encourage you to actually learn > > > > what oo means. A couple of good readings are: > > > > > > > > Structure and Interpretation of Computer Programs. > > > > http://mitpress.mit.edu/sicp/ > > > > > > > > Concepts, Techniques, and Models of Computer Programming. > > > > http://www.info.ucl.ac.be/~pvr/book.html > > > > > > > > Java style (message passing) oo is not the entirety of oo-based > > > > programming! > > > > > > > > Hadley > > > > > > > > -- > > > > http://had.co.nz/ > > > > > > > > > > > > > > > > -- > > > Tom > > > > > >[[alternative HTML version deleted]] > > > > > > __ > > > > > > R-help@r-project.org mailing list > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > > and provide commented, minimal, self-contained, reproducible code. > > > > > > > > > -- > Tom __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Sampling
> I want to generate different samples using the >followindg code: > >g<-sample(LETTERS[1:2], 24, replace=T) > > How can I specify that I need 12 "A"s and 12 "B"s? I introduced the concept of "sampling with minimal replacement" into the S-PLUS version of sample to handle things like this: sample(LETTERS[1:2], 24, minimal = T) This is very useful in variance reduction applications, to approximately stratify but with introducing bias. I'd like to see this in R. I'll raise a related issue - sampling with unequal probabilities, without replacement. R does the wrong thing, in my opinion: > values <- sapply(1:1000, function(i) sample(1:3, size=2, prob = c(.5, .25, > .25))) > table(values) values 1 2 3 834 574 592 The selection probabilities are not proportional to the specified probabilities. In contrast, in S-PLUS: > values <- sapply(1:1000, function(i) sample(1:3, size=2, prob = c(.5, .25, > .25))) > table(values) 1 2 3 1000 501 499 You can specify minimal = FALSE to get the same behavior as R: > values <- sapply(1:1000, function(i) sample(1:3, size=2, prob = c(.5, .25, > .25), minimal = F)) > table(values) 1 2 3 844 592 564 There is a reason this is associated with the concept of sampling with minimal replacement. Consider for example: sample(1:4, size = 3, prob = 1:4/10) The expected frequencies of (1,2,3,4) should be proportional to size*prob = c(.3,.6,.9,1.2). That isn't possible when sampling without replacement. Sampling with minimal replacement allows this; observation 4 is included in every sample, and is included twice in 20% of the samples. Tim Hesterberg Disclaimer - these are my opinions, not those of my employer. | Tim Hesterberg Senior Research Scientist | | [EMAIL PROTECTED] Insightful Corp.| | (206)802-23191700 Westlake Ave. N, Suite 500 | | (206)283-8691 (fax) Seattle, WA 98109-3044, U.S.A. | | www.insightful.com/Hesterberg | I'll teach short courses: Advanced Programming in S-PLUS: San Antonio TX, March 26-27, 2008. Bootstrap Methods and Permutation Tests: San Antonio, March 28, 2008. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] counting row repetitions without loop
On Feb 6, 2008 8:08 AM, Waterman, DG (David)
<[EMAIL PROTECTED]> wrote:
> Hi,
> I have a data frame consisting of coordinates on a 10*10 grid, i.e.
> > example
> x y
> 1 4 5
> 2 6 7
> 3 6 6
> 4 7 5
> 5 5 7
> 6 6 7
> 7 4 5
> 8 6 7
> 9 7 6
> 10 5 6
> What I would like to do is return an 10*10 matrix consisting of counts
> at each position, so in the above example I would have a matrix where,
> for example, cell [4,5] contains 2 and [6,7] contains 3. At the moment I
> have implemented this using a for loop over the rows of the data frame,
> however the data frames I want to process are very long so the loop
> takes many minutes to complete. Can I do this in a more efficient way?
What you are describing is essentially a cross-tabulation so you could use
> examp
x y
1 4 5
2 6 7
3 6 6
4 7 5
5 5 7
6 6 7
7 4 5
8 6 7
9 7 6
10 5 6
> xtabs(~ x + y, examp)
y
x 5 6 7
4 2 0 0
5 0 1 1
6 0 1 3
7 1 1 0
This omits the rows and columns which are completely empty but you can
work around that.
If you have a very large collection of such pairs to summarize you
could consider the version of xtabs in the Matrix package that allows
for the argument sparse = TRUE. That uses conversion of the "triplet"
form of a sparse matrix to the compressed column for to do the
counting.
If you want to do this without converting the integers in 'x' and 'y'
to factors you can use a distinctly unobvious function like
library(Matrix)
sparsetab <- function(x, y)
{
x <- as.integer(x)
y <- as.integer(y)
stopifnot(length(x) == length(y))
lx <- length(x)
mx <- max(x)
my <- max(y)
as(new("dgTMatrix", i = x - 1L, j = y - 1L,
x = rep(1, length(x)), Dim = c(mx, my),
Dimnames = list(1:mx,1:my)), "dgCMatrix")
}
which produces
> with(examp, sparsetab(x, y))
7 x 7 sparse Matrix of class "dgCMatrix"
1 2 3 4 5 6 7
1 . . . . . . .
2 . . . . . . .
3 . . . . . . .
4 . . . . 2 . .
5 . . . . . 1 1
6 . . . . . 1 3
7 . . . . 1 1 .
One reason to use such a function instead of xtabs is because xtabs
will convert 'x' and 'y' to factors and the default ordering of the
levels is lexicographic so '11' occurs before '2'. Again, you can get
around that but the function shown above is more direct and should be
fast enough for most any application.
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Re: [R] inserting text lines in a dat frame
This should do it for you:
x <- read.table(textConnection("V1V2 V3
1 chr1 11255 55
2 chr1 11320 29
3 chr1 11400 45
4 chr2 21680 35
5 chr2 21750 84
6 chr2 21820 29
7 chr2 31890 46
8 chr3 32100 29
9 chr3 52380 29
10 chr3 66450 46" ), header=TRUE)
outfile <- '/tempxx.txt'
cat("browser position chr1:1-1\nrowser hide all\n", file=outfile)
result <- lapply(split(x, x$V1), function(.chro){
cat(sprintf("track type=wiggle_0 name=sample description=%s_sample
visibility=full\nvariableStep chrom=%s span=1\n",
as.character(.chro$V1[1]), as.character(.chro$V1[1])),
file=outfile, append=TRUE)
write.table(.chro[, -1], sep="\t", file=outfile, append=TRUE,
quote=FALSE, col.names=FALSE, row.names=FALSE)
})
On 2/6/08, joseph <[EMAIL PROTECTED]> wrote:
>
> Hi Jim
> yes, this exactly want I want. However, I need one more step to get rid of
> the first column so that the final file looks like this:
> browser position chr1:1-1
> browser hide all
> track type=wiggle_0 name=sample description=chr1_sample visibility=full
> variableStep chrom=chr1 span=1
> 11255 55
> 11320 29
> 11400 45
> track type=wiggle_0 name=sample description=chr2_sample visibility=full
> variableStep chrom=chr2 span=1
> 21680 35
> 21750 84
> 21820 29
> track type=wiggle_0 name=sample description=chr3_sample visibility=full
> variableStep chrom=chr3 span=1
> 32100 29
> 32170 45
> 32240 45
> Thank you very much
> - Original Message
> From: jim holtman <[EMAIL PROTECTED]>
> To: joseph <[EMAIL PROTECTED]>
> Cc: r-help@r-project.org
> Sent: Wednesday, February 6, 2008 2:37:38 AM
> Subject: Re: inserting text lines in a dat frame
>
> Try this and see if it is what you want:
>
> x <- read.table(textConnection("V1V2 V3
> 1 chr1 11255 55
> 2 chr1 11320 29
> 3 chr1 11400 45
> 4 chr2 21680 35
> 5 chr2 21750 84
> 6 chr2 21820 29
> 7 chr2 31890 46
> 8 chr3 32100 29
> 9 chr3 52380 29
> 10 chr3 66450 46" ), header=TRUE)
> cat("browser position chr1:1-1\nrowser hide all\n", file='tempxx.txt')
> result <- lapply(split(x, x$V1), function(.chro){
> cat(sprintf("track type=wiggle_0 name=sample description=%s_sample
> visibility=full\nvariableStep chrom=%s span=1\n",
> as.character(.chro$V1[1]), as.character(.chro$V1[1])),
> file="tempxx.txt", append=TRUE)
> write.table(.chro, sep="\t", file="tempxx.txt", append=TRUE,
> col.names=FALSE, row.names=FALSE)
> })
>
>
>
> On Feb 5, 2008 11:22 PM, joseph <[EMAIL PROTECTED]> wrote:
> >
> >
> >
> >
> >
> > Hi Jim
> > I am trying to prepare a bed file to load as accustom track on the UCSC
> > genome browser.
> > I have a data frame that looks like the one below.
> > > x
> > V1V2 V3
> > 1 chr1 11255 55
> > 2 chr1 11320 29
> > 3 chr1 11400 45
> > 4 chr2 21680 35
> > 5 chr2 21750 84
> > 6 chr2 21820 29
> > 7 chr2 31890 46
> > 8 chr3 32100 29
> > 9 chr3 52380
> > 29
> > 10 chr3 66450 46
> > I would like to insert the following 4 lines at the beginning:
> > browser position chr1:1-1
> > browser hide all
> > track type=wiggle_0 name=sample description=chr1_sample visibility=full
> > variableStep chrom=chr1 span=1
> > and then insert 2 lines before each chromosome:
> > track type=wiggle_0 name=sample description=chr2_sample visibility=full
> > vriableStep chrom=chr2 span=1
> > The final result should be tab delimited file that looks like this:
> > browser position chr1:1-1
> > browser hide all
> > track type=wiggle_0 name=sample description=chr1_sample visibility=full
> > variableStep chrom=chr1 span=1
> > chr1 11255 55
> > chr1 11320 29
> > chr1 11400 45
> > track type=wiggle_0 name=sample description=chr2_sample visibility=full
> > variableStep chrom=chr2 span=1
> > chr2 21680 35
> > chr2 21750 84
> > chr2 21820 29
> > track type=wiggle_0 name=sample description=chr3_sample visibility=full
> > variableStep chrom=chr3
> > span=1
> > chr3 32100 29
> > chr3 32170 45
> > chr3 32240 45
> > Any kind of help or guidance will be much appreciated.
> > Joseph
> >
> >
> > Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it
> > now.
>
>
>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 646 9390
>
> What is the problem you are trying to solve?
>
>
>
> Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it
> now.
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
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[R] RSF
how can i compare a cox model and a rsf? someone can tell me how to do that in R? Thanks [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] axis help
On Wednesday 06 February 2008 (15:14:28), [EMAIL PROTECTED] wrote: > Hi, i'm having trouble with my x and y axis. The commands i'm using are >below. The problem is that the y axis starts at coordinate 0,1 and the x >axis starts at coordinate 0,0. As far as I know the y axis can't start > at 0 (because it's log scaled) ,so I would like to position the x axis at > 0,1 but don't know how to do this. Could anyone advise? >axis(1,at=c(0,0.6,1.1,1.6,2.1,2.6,3.1,3.6),labels=c(0,3,4,5,6,7,8,NA)) >axis(2) Try: axis(1,at=c(0,0.6,1.1,1.6,2.1,2.6,3.1,3.6),labels=c(0,3,4,5,6,7,8,NA),pos=1) The 'pos=' argument does the trick. Best, Martin __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Sampling
Tim Hesterberg wrote: >> values <- sapply(1:1000, function(i) sample(1:3, size=2, prob = c(.5, .25, >> .25))) >> table(values) >> > values > 1 2 3 > 834 574 592 > > The selection probabilities are not proportional to the specified > probabilities. > > In contrast, in S-PLUS: > >> values <- sapply(1:1000, function(i) sample(1:3, size=2, prob = c(.5, .25, >> .25))) >> table(values) >> > 1 2 3 > 1000 501 499 > > But is that the right thing? If you can use prob=c(.6, .2, .2) and get 1200 - 400 - 400, then I'm not going to play poker with you The interpretation in R is that you are dealing with "fat cards", i.e. card 1 is twice as thick as the other two, so there is 50% chance of getting the _first_ card as a 1 and additionally, (.25+.25)*2/3 to get the 2nd card as a 1 for a total of .8333. And since the two cards are different the expected number of occurrences of card 1 in 1000 samples is 833. What is the interpretation in S-PLUS? -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] filling data into objects
I am trying to generate artificial data for feature selection. Basically trying to generate a total of 1000 features with 100 that are informative and rest are uninformative. Informative.data.class1<-rnorm(100,0.25,1) Uninformative.data.class1<-rnorm(900,0,1) Informative.data.class2<-rnorm(100, -0.25,1) Uninformative.data.class2<-rnorm(900,0,1) The above will give me one set of data for the two classes. I am interested in generating about a 100 set for each class. What is a neat way to write it in R? Thanks ../Murli [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Discriminant function analysis
On 2008-02-06, Birgit Lemcke <[EMAIL PROTECTED]> wrote: > > I am using R 2.6.1 on a PowerBook G4. > I would like to perform a discriminant function analysis. I found lda > in MASS but as far as I understood, is it only working with > explanatory variables of the class factor. I think you are mistaken. If you reread the help for lda() you'll see that the grouping has to be a factor, but the explanatory variables should be numeric. > My dataset contains variables of the classes factor and numeric. Is > there another function that is able to handle this? The numeric variables are fine. The factor variables may have to be recoded into dummy binary variables, I'm not sure if lda() will deal with them properly otherwise. HTH, Tyler __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] box.Cox.powers() warning
Dear Clara, The warning is nothing to worry about. If start values aren't specified, box.cox.powers() uses optimize() to find start values for each transformation parameter (in this case, there's only one) prior to using optim() to maximize the (possibly multivariate) likelihood. In the course of finding start values, optimize() apparently tried an unreasonable value. In this case, box.cox.powers(income, start=1) gives you the same result minus the warning. Regards, John John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario, Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox > -Original Message- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > project.org] On Behalf Of [EMAIL PROTECTED] > Sent: February-06-08 1:05 PM > To: R-help@r-project.org > Subject: [R] box.Cox.powers() warning > > Dear Rlist, > > Using an example in box.cox.powers() help, I have the following warning > message. > > example: > library(car) > >attach(Prestige) > > > box.cox.powers(income) > Box-Cox Transformation to Normality > > Est.Power Std.Err. Wald(Power=0) Wald(Power=1) > 0.1793 0.11081.6179 -7.4062 > > L.R. test, power = 0: 2.7103 df = 1 p = 0.0997 > L.R. test, power = 1: 47.261 df = 1 p = 0 > Warning message: > In optimize(f = function(lambda) univ.neg.kernel.logL(x = X[, j], : > NA/Inf replaced by maximum positive value > > I do not know the reason for such warning message. > Can someone help me on this matter? > > Best regards, > Clara Cordeiro > > > sessionInfo() > R version 2.6.1 (2007-11-26) > i386-pc-mingw32 > > locale: > LC_COLLATE=Portuguese_Portugal.1252;LC_CTYPE=Portuguese_Portugal.1252;L > C_MONETARY=Portuguese_Portugal.1252;LC_NUMERIC=C;LC_TIME=Portuguese_Por > tugal.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] nnet_7.2-38car_1.2-7 MASS_7.2-38FitAR_1.0 > leaps_2.7 > [6] lattice_0.17-2 > > loaded via a namespace (and not attached): > [1] grid_2.6.1 tools_2.6.1 > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] filling data into objects
Perhaps:
for(i in 1:100)assign(sprintf("Informative.data.class%s", i),
rnorm(100, 0.25,1))
for(i in 1:100)assign(sprintf("Uninformative.data.class%s", i), rnorm(900))
Or working with a list:
Informative <- replicate(100, rnorm(100, 0.25,1))
Uninformative <- replicate(100, rnorm(900))
On 06/02/2008, Nair, Murlidharan T <[EMAIL PROTECTED]> wrote:
> I am trying to generate artificial data for feature selection. Basically
> trying to generate a total of 1000 features with 100 that are informative and
> rest are uninformative.
> Informative.data.class1<-rnorm(100,0.25,1)
> Uninformative.data.class1<-rnorm(900,0,1)
> Informative.data.class2<-rnorm(100, -0.25,1)
> Uninformative.data.class2<-rnorm(900,0,1)
>
> The above will give me one set of data for the two classes. I am interested
> in generating about a 100 set for each class. What is a neat way to write it
> in R?
> Thanks ../Murli
>
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
__
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and provide commented, minimal, self-contained, reproducible code.
[R] lme predicted value confidence intervals
Dear R users, Does anyone know of a way to obtain approximate 95% confidence intervals for predicted values for factor levels of fixed effects from lme? Our goal is to use these intervals to interpret patterns across our predicted values for certain factor levels. Our mixed model has the following form with 7 levels of mtDNA, 2 levels of autosome, 2 levels of brood and 2 levels of block, > lme(fitness ~ mtDNA*autosome + brood, random = ~1 | block) We have used the predict.lme function to obtain predicted values, but are unsure how to obtain appropriate standard errors on these predicted values. Using predict.lme to predict "fitness" across a subset of our factor levels (2 mtDNA, 2 autosome) generates the following output, autosome mtDNA brood block predict.fixed predict.block 1 ore ore A A 0.4977047 0.5016255 2 ore simw501 A A 0.4278287 0.4317495 3 ore ore B A 0.5042857 0.5082065 4 ore simw501 B A 0.4344098 0.4383306 5 ore ore A B 0.4977047 0.4937839 6 ore simw501 A B 0.4278287 0.4239079 7 ore ore B B 0.5042857 0.5003649 8 ore simw501 B B 0.4344098 0.4304890 9 aut ore A A 0.5321071 0.5360279 10 aut simw501 A A 0.4866497 0.4905705 11 aut ore B A 0.5386882 0.5426090 12 aut simw501 B A 0.4932308 0.4971516 13 aut ore A B 0.5321071 0.5281863 14 aut simw501 A B 0.4866497 0.4827289 15 aut ore B B 0.5386882 0.5347674 16 aut simw501 B B 0.4932308 0.4893099 We would like to calculate, for example, the appropriate 95% confidence intervals for the predicted values of autosome=ore + mtDNA=ore, autosome=ore + mtDNA=simw501, etc. Sincerely, Kristi Montooth and Colin Meiklejohn Ecology and Evolutionary Biology Brown University __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] filling data into objects
Oh yes, that's what I was looking for. I can then do a
Class1<-rbind(Informative.data, Uninformative.data)
Thanks ../Murli
-Original Message-
From: Henrique Dallazuanna [mailto:[EMAIL PROTECTED]
Sent: Wednesday, February 06, 2008 3:06 PM
To: Nair, Murlidharan T
Cc: [EMAIL PROTECTED]
Subject: Re: [R] filling data into objects
Perhaps:
for(i in 1:100)assign(sprintf("Informative.data.class%s", i),
rnorm(100, 0.25,1))
for(i in 1:100)assign(sprintf("Uninformative.data.class%s", i), rnorm(900))
Or working with a list:
Informative <- replicate(100, rnorm(100, 0.25,1))
Uninformative <- replicate(100, rnorm(900))
On 06/02/2008, Nair, Murlidharan T <[EMAIL PROTECTED]> wrote:
> I am trying to generate artificial data for feature selection. Basically
> trying to generate a total of 1000 features with 100 that are informative and
> rest are uninformative.
> Informative.data.class1<-rnorm(100,0.25,1)
> Uninformative.data.class1<-rnorm(900,0,1)
> Informative.data.class2<-rnorm(100, -0.25,1)
> Uninformative.data.class2<-rnorm(900,0,1)
>
> The above will give me one set of data for the two classes. I am interested
> in generating about a 100 set for each class. What is a neat way to write it
> in R?
> Thanks ../Murli
>
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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Re: [R] Sampling
>Tim Hesterberg wrote: >>I'll raise a related issue - sampling with unequal probabilities, >>without replacement. R does the wrong thing, in my opinion: >>... >Peter Dalgaard wrote: >But is that the right thing? ... (See bottom for more of the previous messages.) First, consider the common case, where size * max(prob) < 1 -- sampling with unequal probabilities without replacement. Why do people do sampling with unequal probabilities, without replacement? A typical application would be sampling with probability proportional to size, or more generally where the desire is that selection probabilities match some criterion. The default S-PLUS algorithm does that. The selection probabilities at each of step 1, 2, ..., size are all equal to prob, and the overall probabilities of selection are size*prob. The R algorithm (and old S+ algorithm, prior to S+6.2) did not; at step 1 the selection probabilities are correct, but not in subsequent steps. With size = 2 and prob = c(.5, .25, .25), for example, the selection probabilities at step 2 are (.33, .33, .33). The R/old S+ algorithm is the result of programming "sampling with probability proportional to prob without replacement" literally, sampling greedily at each step, ignoring dependence, without thinking about that fact that that doesn't give the desired unconditional probabilities after step 1. In practice one often needs to know the actual selection probabilities, and they are difficult to compute except in toy problems with small size. Now turn to the less common case -- possible overselection -- sampling with unequal probabilities with minimal replacement. One example of this would be in multistage sampling. At stage one you select cities with probability proportional to prob. If size*max(prob) > 1, then a city may be selected more than once. If selected more than once, the second stage selects that many individuals from the city. Another example of both cases is an improvement on SIR (sampling-importance-resampling). In Bayesian simulation, if importance sampling is used, each observation ends up with a value and a weight. Often one would prefer the output to be a sample without weights. In SIR this is done by sampling from the observations with probability proportional to the weight, <>. As a result some observations may be sampled multiple times. It would be better to do this with minimal replacement. If size*max(prob) <= 1 then no observation is sampled multiple times. If size*max(prob) > 1 then some observations may be sampled multiple times, but there will tend to be less of this (and more unique values sampled) than if sampling with replacement. Here's a final example of the less common case. This one is more colorful, but a bit long; at the end I'll relate this to another improvement on SIR. "Splitting" and "Russian Roulette" are complementary techniques that date back to the early days of Monte Carlo simulation, developed for estimating the probability of neutrons or other particles penetrating a shield. The simplest procedure is to generate a bunch of random neutrons, and follow each on its path through the shield - it flies a random distance until it hits an atom, there is a certain probability of absorption, otherwise it is reflected in a random direction, etc. In the end you count the proportion of neutrons that penetrate. The problem is that the penetration probability is so small that a you have to start simulating with an enormous number of neutrons, to accurately estimate the small probability. The next improvement is to bias the sampling, and assign each neutron a weight. The weight W starts at 1. When the neutron hits an atom, instead of being absorbed with probability p, multiply W by p. You can also bias the direction, in favor of of the direction of the shield boundary, and counteract that sampling bias by multiplying W by the relative likelihood (likelihood of observed direction under random sampling / likelihood under biased sampling). As a neutron proceeds its W keeps getting up-weighted and down-weighted. The final estimate of penetration is based on the average W. The problem with this is that the variance of W across neutrons can be huge; most W's are very small, and a few are much larger than the others. That is where Russian roulette and splitting come in. In the middle of a simulated path, if a neutron has a very small W, it undergoes Russian roulette - there is a probability P that it is killed; if not killed its weight is divided by (1-P). Conversely, if the W is relatively large, the particle is split into K simulated particles, each with initial weight W/K, which are subsequently simulated independently. The two techniques together reduce the variance of W across neutrons. Sampling with unequal probabilities and minimal replacement can be used to similar effect. Sample from the current population of particles with probabilities proportional to 'prob', then divide each particle's W
[R] "Inverting" a list
Is there a built in function to invert a list? i.e. to go from
list(
a = c("1", "2", "3"),
b = c("1"),
d = c("2", "4")
)
to
list(
"1" = c("a", "b"),
"2" = c("a", "d"),
"3" = "a",
"4" = "2"
)
Hadley
--
http://had.co.nz/
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] "Inverting" a list
This isn't a single command but its pretty short:
unstack(stack(L)[2:1])
On Feb 6, 2008 5:51 PM, hadley wickham <[EMAIL PROTECTED]> wrote:
> Is there a built in function to invert a list? i.e. to go from
>
> list(
> a = c("1", "2", "3"),
> b = c("1"),
> d = c("2", "4")
> )
>
> to
>
> list(
> "1" = c("a", "b"),
> "2" = c("a", "d"),
> "3" = "a",
> "4" = "2"
> )
>
> Hadley
>
> --
> http://had.co.nz/
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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Re: [R] "Inverting" a list
A more primitive method is about 5 times faster than Gabor's.
L <- list(
a = c("1", "2", "3"),
b = c("1"),
d = c("2", "4")
)
system.time(
for (i in 1:100)
{t1 <- unlist(L)
names(t1) <- rep(names(L), lapply(L, length))
tapply(names(t1), t1, c)
}
)
system.time(
for (i in 1:100)
unstack(stack(L)[2:1])
)
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Re: [R] how to plot an user-defined function
Thank all of you for your helps. They are very helpful.
But I have a further question. Suppose I have the following mixed effect
model
thetaMixed <- function(tau, i)
{
w <- 1 / (s^2 + tau^2)
mu <- sum(theta * w) / sum(w)
b <- s[i]^2 / (s[i]^2 + tau^2)
theta[i]*(1-b) + mu*b)
}
I want draw all the mixed effects in a single figure using
for (i in 1:10)
{
plot(Vectorize(thetaMixed), 0, 2, i=i)
}
and hope plot will recognize that i is the argument for function thetaMixed,
and 0, 2 are the range for tau. But it fails.
Could anyone kindly help me on this issue?
Thanks
On Feb 5, 2008 10:45 PM, Duncan Murdoch <[EMAIL PROTECTED]> wrote:
> jim holtman wrote:
> > Your function 'll' only returns a single value when passed a vector:
> >
> >
> >> x <- seq(0,2,.1)
> >> ll(x)
> >>
> > [1] -7.571559
> >
> >
> > 'plot' expects to pass a vector to the function and have it return a
> > vector of the same length; e.g.,
> >
> >
> >> sin(x)
> >>
> > [1] 0. 0.09983342 0.19866933 0.29552021 0.38941834 0.47942554
> > 0.56464247 0.64421769 0.71735609
> > [10] 0.78332691 0.84147098 0.89120736 0.93203909 0.96355819 0.98544973
> > 0.99749499 0.99957360 0.99166481
> > [19] 0.97384763 0.94630009 0.90929743
> >
> >
> > So you either have to rewrite your function, or have a loop that will
> > evaluate the function at each individual point and then plot it.
> >
> Or use Vectorize, e.g.
>
> plot(Vectorize(ll), 0, 2)
>
> Duncan Murdoch
> > On Feb 5, 2008 7:06 PM, John Smith <[EMAIL PROTECTED]> wrote:
> >
> >> Dear R-users,
> >>
> >> Suppose I have defined a likelihood function as ll(tau), how can I plot
> this
> >> likelihood function by calling it by plot?
> >>
> >> I want to do it like this:
> >>
> >> ll <- function(tau)
> >> {
> >>w <- 1 / (s^2 + tau^2)
> >>mu <- sum(theta * w) / sum(w)
> >>-1/2*sum((theta-mu)^2*w -log(w))
> >> }
> >> plot(ll, 0, 2)
> >>
> >>
> >>
> >> But have the following error:
> >> Error in xy.coords(x, y, xlabel, ylabel, log) :
> >> 'x' and 'y' lengths differ
> >> In addition: Warning messages:
> >> 1: In s^2 + tau^2 :
> >> longer object length is not a multiple of shorter object length
> >> 2: In theta * w :
> >> longer object length is not a multiple of shorter object length
> >> 3: In (theta - mu)^2 * w :
> >> longer object length is not a multiple of shorter object length
> >>
> >>
> >> Thanks
> >>
> >>[[alternative HTML version deleted]]
> >>
> >> __
> >> R-help@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >>
> >
> >
> >
> >
>
>
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[R] time series plot
Dear all. I want to add a vertical line in my time series series plot. If i had an anual data I do: plot(data,v="2008"), but if I want to add a vertical line in fisrt quarter of 2008, how can i do? Thanks a lot Ana -- __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] matrix loop
Dear list,
I'm trying to make a loop of a (5x10) matrix and below are my codes. Could
anybody help me figure out why my loop is not working. Thanks in advance!!
m<-1:5
n<-1:10
for(i in 1:length(m))
{ for(j in 1:length(n))
{
y[i,j]=sum(i,j)
y<-as.matrix(y[i,j])
}
}
cheers,
Anisah
-
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Re: [R] time series plot
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. > It all depends on how you constructed the x-axis. You can try abline(v=2008.25) On Feb 6, 2008 6:41 PM, Ana Quitério <[EMAIL PROTECTED]> wrote: > Dear all. > > I want to add a vertical line in my time series series plot. > If i had an anual data I do: > plot(data,v="2008"), but if I want to add a vertical line in fisrt quarter > of 2008, how can i do? > > Thanks a lot > > Ana > -- > > __ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem you are trying to solve? __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] matrix loop
What exactly are you intending the loop to do? Why do you have the
'as.matrix' in the middle of the loop? Where was 'y' defined? Does
this do what you want?
> outer(1:5, 1:10, "+")
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]23456789 1011
[2,]3456789 10 1112
[3,]456789 10 11 1213
[4,]56789 10 11 12 1314
[5,]6789 10 11 12 13 1415
On Feb 6, 2008 7:52 PM, mohamed nur anisah <[EMAIL PROTECTED]> wrote:
> Dear list,
>
> I'm trying to make a loop of a (5x10) matrix and below are my codes. Could
> anybody help me figure out why my loop is not working. Thanks in advance!!
>
>
> m<-1:5
> n<-1:10
> for(i in 1:length(m))
> { for(j in 1:length(n))
> {
> y[i,j]=sum(i,j)
> y<-as.matrix(y[i,j])
> }
> }
> cheers,
> Anisah
>
>
> -
>
>[[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
__
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[R] Res: gc() and memory efficiency
Dear Harold,
I had the same problem some times ago. I noticed that after I run a set
commands (cleaning all non-usefull variables) for 5 times, the system
broken-down. I solved it building several scritpsNN.R and call them in a .BAT
DOS file. It worked so fine, almost in my case, and the computer runned for
several days without stop :-)
If you need more info on this solutions, fill free to write me again.
By other side, if you find a better solutions (I also unfortunatelly run
windows), share with us.
Kind regards
Miltinho
Brazil
- Mensagem original
De: Prof Brian Ripley <[EMAIL PROTECTED]>
Para: "Doran, Harold" <[EMAIL PROTECTED]>
Cc: r-help@r-project.org
Enviadas: Terça-feira, 5 de Fevereiro de 2008 3:06:51
Assunto: Re: [R] gc() and memory efficiency
1) See ?"Memory-limits": it is almost certainly memory fragmentation.
You don't need to give the memory back to the OS (and few OSes actually do
so).
2) I've never seen this running a 64-bit version of R.
3) You can easily write a script to do this. Indeed, you could write an R
script to run multiple R scripts in separate processes in turn (via
system("Rscript fileN.R") ). For example. Uwe Ligges uses R to script
building and testing of packages on Windows.
On Mon, 4 Feb 2008, Doran, Harold wrote:
> I have a program which reads in a very large data set, performs some
> analyses, and then repeats this process with another data set. As soon
> as the first set of analyses are complete, I remove the very large
> object and clean up to try and make memory available in order to run the
> second set of analyses. The process looks something like this:
>
> 1) read in data set 1 and perform analyses
> rm(list=ls())
> gc()
> 2) read in data set 2 and perform analyses
> rm(list=ls())
> gc()
> ...
>
> But, it appears that I am not making the memory that was consumed in
> step 1 available back to the OS as R complains that it cannot allocate a
> vector of size X as the process tries to repeat in step 2.
>
> So, I close and reopen R and then drop in the code to run the second
> analysis. When this is done, I close and reopen R and run the third
> analysis.
>
> This is terribly inefficient. Instead I would rather just source in the
> R code and let the analyses run over night.
>
> Is there a way that I can use gc() or some other function more
> efficiently rather than having to close and reopen R at each iteration?
>
> I'm using Windows XP and r 2.6.1
>
> Harold
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford,Tel: +44 1865 272861 (self)
1 South Parks Road,+44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
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para armazenamento!
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