Re: [R] MDS in 3D
Oh, it was nearer than I have thought! Thanks. Atte I have tried to develop multidimensional scaling for 3D space using PCA without success, yet;-) Is there some application ready in R? Yes. stats has cmdscale. MASS has sammon and isoMDS. All three have a 'k' argument to determine the output dimension. -- 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 __ R-help@stat.math.ethz.ch 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] ifelse on data frames
[EMAIL PROTECTED] said the following on 2007-01-05 04:18: [Using R 2.2.0 on Windows XP; OK, OK, I will update soon!] I have noticed some undesirable behaviour when applying ifelse to a data frame. Here is my code: A - scan() 1.00 0.00 0.00 0 0.0 0.027702 0.972045 0.000253 0 0.0 A - matrix(A,nrow=2,ncol=5,byrow=T) A == 0 ifelse(A==0,0,-A*log(A)) A - as.data.frame(A) ifelse(A==0,0,-A*log(A)) How about using sapply(A, function(x) ifelse(x == 0, 0, -x*log(x))) ? HTH, Henric and this is the output: A - scan() 1: 1.00 0.00 0.00 0 0.0 6: 0.027702 0.972045 0.000253 0 0.0 11: Read 10 items A - matrix(A,nrow=2,ncol=5,byrow=T) A == 0 [,1] [,2] [,3] [,4] [,5] [1,] FALSE TRUE TRUE TRUE TRUE [2,] FALSE FALSE FALSE TRUE TRUE ifelse(A==0,0,-A*log(A)) [,1] [,2][,3] [,4] [,5] [1,] 0. 0. 0.000 [2,] 0.09934632 0.02756057 0.00209537700 A - as.data.frame(A) ifelse(A==0,0,-A*log(A)) [[1]] [1] 0. 0.09934632 [[2]] [1]NaN 0.02756057 [[3]] [1] 0 [[4]] [1] NaN NaN [[5]] [1] 0 [[6]] [1] 0. 0.09934632 [[7]] [1] 0 [[8]] [1] 0 [[9]] [1] 0 [[10]] [1] 0 Is this a bug or a feature? Can the behaviour be explained? Regards, Murray Jorgensen __ R-help@stat.math.ethz.ch 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] Scripts to plot Taylor Diagram in R
Dear All, Are there any existing scripts to plot Taylor Diagram (definition see http://www.ipsl.jussieu.fr/~jmesce/Taylor_diagram/taylor_diagram_definition.html) ? Thanks a lot! Linda [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] Plot .jpeg image in margins?
Is it possible to plot an image (currently a jpeg) in the margins? Thanks, Kari [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] Contrasts for ordered factors
Dear all,
I do not seem to grasp how contrasts are set for ordered factors. Perhaps
someone can elighten me?
When I work with ordered factors, I would often like to be able to reduce the
used polynomial to a simpler one (where possible). Thus, I would like to
explicetly code the polynomial but ideally, the intial model (thus, the full
polynomial) would be identical to one with an ordered factor.
Here is a toy example with an explanatory variable (EV) with three distinct
values (1 to 3) and a continuous response variable (RV):
options (contrasts= c ('contr.treatment', 'contr.poly'))
example.df - data.frame (EV= rep (1:3, 5))
set.seed (298)
example.df$RV - 2 * example.df$EV + rnorm (15)
I evaluate this data using either an ordered factor or a polynomial with a
linear and a quadratic term:
lm.ord - lm (RV ~ ordered (EV), example.df)
lm.pol - lm (RV ~ EV + I(EV^2), example.df)
I then see that the estimated coefficients differ (and in other examples that I
have come across, it is often even more extreme):
coef (lm.ord)
(Intercept) ordered(EV).L ordered(EV).Q
3.9497767 2.9740535-0.1580798
coef (lm.pol)
(Intercept)EV I(EV^2)
-0.9015283 2.8774032-0.1936074
but the predictions are the same (except for some rounding):
table (round (predict (lm.ord), 6) == round (predict (lm.pol), 6))
TRUE
15
I thus conclude that the two models are the same and are just using a different
parametrisation. I can easily interprete the parameters of the explicit
polynomial but I started to wonder about the parametrisation of the ordered
factor. In search of an answer, I did check the contrasts:
contr.poly (levels (ordered (example.df$EV)))
.L .Q
[1,] -7.071068e-01 0.4082483
[2,] -9.073264e-17 -0.8164966
[3,] 7.071068e-01 0.4082483
The linear part basically seems to be -0.707, 0 (apart for numerical rounding)
and 0.707. I can understand that any even-spaced parametrisation is possible
for the linear part. But does someone know where the value of 0.707 comes from
(it seems to be the square-root of 0.5, but why?) and why the middle term is
not exactly 0?
I do not understand the quadratic part at all. Wouldn't that need the be the
linear part to the power of 2?
Thank you for your thoughts! Lorenz
-
Lorenz Gygax
Swiss Federal Veterinary Office
Centre for proper housing of ruminants and pigs
Tänikon, CH-8356 Ettenhausen / Switzerland
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[R] tapply, how to get level information
Hello,
I'm applying a self-written function to a matrix on basis of different
levels.
Is there any way, to get the level information within the self-written
function???
t - tapply(mat, levels, plotDensity)
plotDensity - function(x) {
??? print(level(x)) ???
}
Antje
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[R] Speeding things up
Hi,
is it possible to do this operation faster? I am going over 35k data
entries and this takes quite some time.
for(cnt in 2:length(sdata$date))
{
if(sdata$value[cnt] sdata$value[cnt - 1]) {
sdata$ddtd[cnt] - sdata$ddtd[cnt - 1] +
sdata$value[cnt - 1] -
sdata$value[cnt]
}
else sdata$ddtd[cnt] - 0
}
return(sdata)
Thank you,
Benjamin
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Re: [R] Contrasts for ordered factors
contr.poly is using orthoogonal polynomials: look at poly() for
further information. It seems to me that you did not realize that,
or did not realize what they are, or ... and that may be enough of
a hint for you or you may need more help, in which case please ask
again.
[EMAIL PROTECTED] wrote:
Dear all,
I do not seem to grasp how contrasts are set for ordered factors. Perhaps
someone can elighten me?
When I work with ordered factors, I would often like to be able to reduce the
used polynomial to a simpler one (where possible). Thus, I would like to
explicetly code the polynomial but ideally, the intial model (thus, the full
polynomial) would be identical to one with an ordered factor.
Here is a toy example with an explanatory variable (EV) with three distinct
values (1 to 3) and a continuous response variable (RV):
options (contrasts= c ('contr.treatment', 'contr.poly'))
example.df - data.frame (EV= rep (1:3, 5))
set.seed (298)
example.df$RV - 2 * example.df$EV + rnorm (15)
I evaluate this data using either an ordered factor or a polynomial with a
linear and a quadratic term:
lm.ord - lm (RV ~ ordered (EV), example.df)
lm.pol - lm (RV ~ EV + I(EV^2), example.df)
I then see that the estimated coefficients differ (and in other examples that
I have come across, it is often even more extreme):
coef (lm.ord)
(Intercept) ordered(EV).L ordered(EV).Q
3.9497767 2.9740535-0.1580798
coef (lm.pol)
(Intercept)EV I(EV^2)
-0.9015283 2.8774032-0.1936074
but the predictions are the same (except for some rounding):
table (round (predict (lm.ord), 6) == round (predict (lm.pol), 6))
TRUE
15
I thus conclude that the two models are the same and are just using a
different parametrisation. I can easily interprete the parameters of the
explicit polynomial but I started to wonder about the parametrisation of the
ordered factor. In search of an answer, I did check the contrasts:
contr.poly (levels (ordered (example.df$EV)))
.L .Q
[1,] -7.071068e-01 0.4082483
[2,] -9.073264e-17 -0.8164966
[3,] 7.071068e-01 0.4082483
The linear part basically seems to be -0.707, 0 (apart for numerical
rounding) and 0.707. I can understand that any even-spaced parametrisation is
possible for the linear part. But does someone know where the value of 0.707
comes from (it seems to be the square-root of 0.5, but why?) and why the
middle term is not exactly 0?
I do not understand the quadratic part at all. Wouldn't that need the be the
linear part to the power of 2?
Thank you for your thoughts! Lorenz
-
Lorenz Gygax
Swiss Federal Veterinary Office
Centre for proper housing of ruminants and pigs
Tänikon, CH-8356 Ettenhausen / Switzerland
__
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Re: [R] Contrasts for ordered factors
[EMAIL PROTECTED] wrote:
Dear all,
I do not seem to grasp how contrasts are set for ordered factors. Perhaps
someone can elighten me?
When I work with ordered factors, I would often like to be able to reduce the
used polynomial to a simpler one (where possible). Thus, I would like to
explicetly code the polynomial but ideally, the intial model (thus, the full
polynomial) would be identical to one with an ordered factor.
Here is a toy example with an explanatory variable (EV) with three distinct
values (1 to 3) and a continuous response variable (RV):
options (contrasts= c ('contr.treatment', 'contr.poly'))
example.df - data.frame (EV= rep (1:3, 5))
set.seed (298)
example.df$RV - 2 * example.df$EV + rnorm (15)
I evaluate this data using either an ordered factor or a polynomial with a
linear and a quadratic term:
lm.ord - lm (RV ~ ordered (EV), example.df)
lm.pol - lm (RV ~ EV + I(EV^2), example.df)
I then see that the estimated coefficients differ (and in other examples that
I have come across, it is often even more extreme):
coef (lm.ord)
(Intercept) ordered(EV).L ordered(EV).Q
3.9497767 2.9740535-0.1580798
coef (lm.pol)
(Intercept)EV I(EV^2)
-0.9015283 2.8774032-0.1936074
but the predictions are the same (except for some rounding):
table (round (predict (lm.ord), 6) == round (predict (lm.pol), 6))
TRUE
15
I thus conclude that the two models are the same and are just using a
different parametrisation. I can easily interprete the parameters of the
explicit polynomial but I started to wonder about the parametrisation of the
ordered factor. In search of an answer, I did check the contrasts:
contr.poly (levels (ordered (example.df$EV)))
.L .Q
[1,] -7.071068e-01 0.4082483
[2,] -9.073264e-17 -0.8164966
[3,] 7.071068e-01 0.4082483
The linear part basically seems to be -0.707, 0 (apart for numerical
rounding) and 0.707. I can understand that any even-spaced parametrisation is
possible for the linear part. But does someone know where the value of 0.707
comes from (it seems to be the square-root of 0.5, but why?) and why the
middle term is not exactly 0?
I do not understand the quadratic part at all. Wouldn't that need the be the
linear part to the power of 2?
These are orthogonal polynomials.
To see the main point, try
M - cbind(1,contr.poly (3))
M
.L .Q
[1,] 1 -7.071068e-01 0.4082483
[2,] 1 -7.850462e-17 -0.8164966
[3,] 1 7.071068e-01 0.4082483
zapsmall(crossprod(M))
.L .Q
3 0 0
.L 0 1 0
.Q 0 0 1
This parametrization has better numerical properties than the
straightforward 1,x,x^2,... , especially in balanced designs.
(SOAPBOX: Some, including me, feel that having polynomials as default
contrasts for ordered factors is a bit of a design misfeature - It was
inherited from S, but assigning equidistant numerical values to ordered
groups isn't really well-founded, and does become plainly wrong when the
levels are really something like 0, 3, 6, 12, 18, 24 months.)
--
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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Re: [R] different points and lines on the same plot
Hi On 7 Jan 2007 at 9:32, Gabor Grothendieck wrote: Date sent: Sun, 7 Jan 2007 09:32:54 -0500 From: Gabor Grothendieck [EMAIL PROTECTED] To: [EMAIL PROTECTED] [EMAIL PROTECTED] Copies to: r-help@stat.math.ethz.ch Subject:Re: [R] different points and lines on the same plot Try this: matplot(patient[,1], patient[,-1], type = o) Another option is to use plot and lines. first initialise plotting region without any actual plotting plot(patient[,1], patient[,2], type=n, ylim=range(patient[,-1])) then add lines in a cycle for(i in 1:4) lines(patient[,1], patient[,i+1], col=i, lwd=2, lty=i) HTH Petr On 1/7/07, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote: Dear all, I have following data called paitent daypatient1patient4patient5patient6 0 -0.27842688 -0.04080808 -0.41948398 -0.04508318 56 -0.22275425 -0.01767067 -0.30977249 -0.03168185 112 -0.08217659 -0.26209243 -0.29141451 -0.09876170 252 0.08044537 -0.26701769 0.05727087 -0.09663701 where each patient have response values at four time points. I want to plot each patient's values over time on the same plot where the value points are connected by line. That is, the graph will have four lines for the four patients. I tried the program below but couldn't make it work correctly. I'm new beginner and haven't yet learned how functions line and points work together. Hope you can help me out. Thanks for your help, Antonia par(mfrow=c(1,1)) plot(patient[,1],patient[,2], pch=1, type=l,col=1,cex=1,lwd=2, xlab=Days, ylab=Patient response,cex.main =1,font.main= 1, main=NULL) points(patient[,1],patient[,3],col=2,pch=1,cex=1) lines(patient[,1],patient[,3],col=2,lty=1,cex=1) points(patient[,1],patient[,4],col=3,pch=1,cex=1) lines(patient[,1],patient[,4],col=2,lty=2,cex=1) points(patient[,1],patient[,5],col=4,pch=1,cex=1) lines(patient[,1],patient[,5],col=2,lty=1,cex=1) points(patient[,1],patient[,6],col=5,pch=1,cex=1) lines(patient[,1],patient[,6],col=2,lty=1,cex=1) __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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. Petr Pikal [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch 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] ACCESS/Office : connecting
Hi there, How can I connect to a ACCESS (.mdb) file? In fact, I would like to connect to a blank file, write a data.frame as table and after that INSERT records using some insert command. Kind regards, Miltinho Brazil __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] scripts with littler
Hi, I'm trying to write R scripts using littler (under Debian), and was originally using the shebang line: #!/usr/bin/env r However this picks up any .RData file that happens to be lying around, which I find a little disturbing, because it means that the script may not behave the same way on successive invocations. If you drop the /usr/bin/env trick then #!/usr/bin/r --vanilla seems to work, but it also prevents the loading of the libraries in my home directory, some of which I'd like to use. #!/usr/bin/r --no-restore doesn't work at all. Ideally I'd like #!/usr/bin/env r --no-restore Has anyone else been round this loop and can offer advice? Cheers, John. -- Contractor in Cambridge UK -- http://www.aspden.com __ R-help@stat.math.ethz.ch 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] Export dataframe to txt
Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. Thank you, Benjamin __ R-help@stat.math.ethz.ch 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] Speeding things up
First, since you only update the 'ddtd' conditioned on 'value', you
should be able to vectorize removing the loop. I let you figure out
how to do that yourself.
Second, you apply the $ operator multiple times in the loop that
will definitely add some overhead. It should be faster to extract
'value' and 'ddtd' and work with those instead.
/Henrik
On 1/8/07, Benjamin Dickgiesser [EMAIL PROTECTED] wrote:
Hi,
is it possible to do this operation faster? I am going over 35k data
entries and this takes quite some time.
for(cnt in 2:length(sdata$date))
{
if(sdata$value[cnt] sdata$value[cnt - 1]) {
sdata$ddtd[cnt] - sdata$ddtd[cnt - 1] +
sdata$value[cnt - 1] -
sdata$value[cnt]
}
else sdata$ddtd[cnt] - 0
}
return(sdata)
Thank you,
Benjamin
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[R] outsourcing R work
Dear Colleagues, If you have a need to outsource any coding in R please check the web site of the Research Centre for Cheminformatics in Belgrade, Serbia http://www.rcc.org.yu . We have skilled statisticians experienced in R, fluent in English and with work experience in the West. For more information please check our website http://www.rcc.org.yu/outsourcing.htm or contact me. Kind regards, DK - Damjan Krstajic Director Research Centre for Cheminformatics e-mail: [EMAIL PROTECTED] www.rcc.org.yu __ R-help@stat.math.ethz.ch 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] Speeding things up
Thanks for your answers, your help is highly appreciated!
On 1/8/07, Zoltan Kmetty [EMAIL PROTECTED] wrote:
Hi Benjamin!
##TRY THIS: THIS MAYBE MUCH FASTER, BECAUSE ONLY WORK WITH THE IMPORTANAT
ROWS - HOPE NO ERROR IN IT:D
puffer1 - as.matrix(sdata$value)
puffer2 - rbind(as.matrix(puffer1[2:nrow(puffer1),1]),0)
speedy - puffer1 puffer2
speedy - (as.matrix(which(puffer1==TRUE)))+1
sdata$ddtd[]=0
for(cnt in 1:nrow(speedy))
{
sdata$ddtd[speedy[cnt,1]] - sdata$ddtd[(speedy[cnt,1]) - 1] +
sdata$value[(speedy[cnt,1]) - 1] -sdata$value[speedy[cnt,1]]
}
return(sdata)
#Zoltan
2007/1/8, Benjamin Dickgiesser [EMAIL PROTECTED]:
Hi,
is it possible to do this operation faster? I am going over 35k data
entries and this takes quite some time.
for(cnt in 2:length(sdata$date))
{
if(sdata$value[cnt] sdata$value[cnt - 1]) {
sdata$ddtd[cnt] - sdata$ddtd[cnt - 1] +
sdata$value[cnt - 1] -
sdata$value[cnt]
}
else sdata$ddtd[cnt] - 0
}
return(sdata)
Thank you,
Benjamin
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Re: [R] Speeding things up
Hi Benjamin!
##TRY THIS: THIS MAYBE MUCH FASTER, BECAUSE ONLY WORK WITH THE IMPORTANAT
ROWS - HOPE NO ERROR IN IT:D
puffer1 - as.matrix(sdata$value)
puffer2 - rbind(as.matrix(puffer1[2:nrow(puffer1),1]),0)
speedy - puffer1 puffer2
speedy - (as.matrix(which(puffer1==TRUE)))+1
sdata$ddtd[]=0
for(cnt in 1:nrow(speedy))
{
sdata$ddtd[speedy[cnt,1]] - sdata$ddtd[(speedy[cnt,1]) - 1] +
sdata$value[(speedy[cnt,1]) - 1] -sdata$value[speedy[cnt,1]]
}
return(sdata)
#Zoltan
2007/1/8, Benjamin Dickgiesser [EMAIL PROTECTED]:
Hi,
is it possible to do this operation faster? I am going over 35k data
entries and this takes quite some time.
for(cnt in 2:length(sdata$date))
{
if(sdata$value[cnt] sdata$value[cnt - 1]) {
sdata$ddtd[cnt] - sdata$ddtd[cnt - 1] +
sdata$value[cnt - 1] -
sdata$value[cnt]
}
else sdata$ddtd[cnt] - 0
}
return(sdata)
Thank you,
Benjamin
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[[alternative HTML version deleted]]
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Re: [R] Export dataframe to txt
On Mon, 8 Jan 2007 11:17:24 + Benjamin Dickgiesser [EMAIL PROTECTED] wrote: Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. see ?write.table Hth Detlef Thank you, Benjamin __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Export dataframe to txt
?write.table On 08/01/07, Benjamin Dickgiesser [EMAIL PROTECTED] wrote: Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. Thank you, Benjamin __ R-help@stat.math.ethz.ch 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 [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] scripts with littler / subroutines
Hi (again), Another difficulty I'm having is creating a common function (foo, say) to share between two scripts. I've tried making a third file containing the function and then sourcing it with source (foo.R), but that only works if you run the script in the directory where foo.R is. (or if the scripts know where they're installed) The other solutions that occur are copy-and-paste, a preprocessor, or some sort of special-purpose library. I think I like the preprocessor best, but it's still kind of nasty. I have the feeling that I'm probably missing something obvious here! Can anyone help? Cheers, John. -- Contractor in Cambridge UK -- http://www.aspden.com __ R-help@stat.math.ethz.ch 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] Export dataframe to txt
#Try: Write.table(...) #Zoltan 2007/1/8, Benjamin Dickgiesser [EMAIL PROTECTED]: Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. Thank you, Benjamin __ R-help@stat.math.ethz.ch 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. [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] Export dataframe to txt
Hi AFAIK ?sink ?write.table are possible options. HTH Petr On 8 Jan 2007 at 11:17, Benjamin Dickgiesser wrote: Date sent: Mon, 8 Jan 2007 11:17:24 + From: Benjamin Dickgiesser [EMAIL PROTECTED] To: r-help@stat.math.ethz.ch Subject:[R] Export dataframe to txt Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. Thank you, Benjamin __ R-help@stat.math.ethz.ch 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. Petr Pikal [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch 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] Plot .jpeg image in margins?
I am not sure what you mean by in margins, if this is keeping the aspect ration, then the answer is yes. Please check EBImage, http://www.ebi.ac.uk/~osklyar/EBImage/ . The package will allow to read/write images in most image formats, the method image() redefined for the Image class will produce an image plot using R graphics device keeping the aspect ratio and display() can display images with zoom and browse functions. Best regards, Oleg On 08/01/07, Kari [EMAIL PROTECTED] wrote: Is it possible to plot an image (currently a jpeg) in the margins? Thanks, Kari [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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. [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] ACCESS/Office : connecting
Hi, you can use the RODBC pakage for that; see: library(RODBC) ?RODBC ?odbcConnectAccess ?sqlSave Regards, Heinrich. -Ursprüngliche Nachricht- Von: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Im Auftrag von Milton Cezar Ribeiro Gesendet: Montag, 08. Jänner 2007 12:22 An: R-help Betreff: [R] ACCESS/Office : connecting Hi there, How can I connect to a ACCESS (.mdb) file? In fact, I would like to connect to a blank file, write a data.frame as table and after that INSERT records using some insert command. Kind regards, Miltinho Brazil __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] R Training Course in Paris
Mango Solutions are pleased to announce the above course in Paris as part of our schedule for Q1 2007. --- Introduction to R and R Programming - 12th February 2008-14th February --- (Please find a french version of this announcement from http://www.mango-solutions.com/services/rtraining/r_paris_training_07_french.html) * Who Should Attend ? This is a course suitable for beginners and improvers in the R language and is ideal for people wanting an all round introduction to R * Course Goals - To allow attendees to understand the technology behind the R package - Improve attendees programming style and confidence - To enable users to access a wide range of available functionality - To enable attendees to program in R within their own environment - To understand how to embed R routines within other applications * Course Outline 1. Introduction to the R language and the R community 2. The R Environment 3. R data objects 4. Using R functions 5. The apply family of functions 6. Writing R functions 7. Standard Graphics 8. Advanced Graphics 9. R Statistics 10. R Applications The cost of these courses is €1800 for commercial attendees and €850 for academic attendees. A €100 discount will be offered to members of the R Foundation (http://www.r-project.org/foundation/main.html). Should your organization have more than 3 possible attendees why not talk to us about hosting a customized and focused course delivered at your premises? Details of further courses in alternative locations are available at http://www.mango-solutions.com/services/training.html More details about this course : - in french : http://www.mango-solutions.com/services/rtraining/r_paris_training_07_french.html - in english : http://www.mango-solutions.com/services/rtraining/r_paris_training_07.html Should you want to book a place on this course or have any questions please contact [EMAIL PROTECTED] Cordialement, Romain Francois -- Mango Solutions Tel +44 (0)1249 467 467 Mob +44 (0)7813 526 123 Fax +44 (0)1249 467 468 data analysis that delivers __ R-help@stat.math.ethz.ch 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] R Training Course in Paris
Romain Francois wrote: Mango Solutions are pleased to announce the above course in Paris as part of our schedule for Q1 2007. --- Introduction to R and R Programming - 12th February 2008-14th February --- Small typo, the correct date is : 12th February 2007-14th February. Cheers, Romain (Please find a french version of this announcement from http://www.mango-solutions.com/services/rtraining/r_paris_training_07_french.html) * Who Should Attend ? This is a course suitable for beginners and improvers in the R language and is ideal for people wanting an all round introduction to R * Course Goals - To allow attendees to understand the technology behind the R package - Improve attendees programming style and confidence - To enable users to access a wide range of available functionality - To enable attendees to program in R within their own environment - To understand how to embed R routines within other applications * Course Outline 1. Introduction to the R language and the R community 2. The R Environment 3. R data objects 4. Using R functions 5. The apply family of functions 6. Writing R functions 7. Standard Graphics 8. Advanced Graphics 9. R Statistics 10. R Applications The cost of these courses is €1800 for commercial attendees and €850 for academic attendees. A €100 discount will be offered to members of the R Foundation (http://www.r-project.org/foundation/main.html). Should your organization have more than 3 possible attendees why not talk to us about hosting a customized and focused course delivered at your premises? Details of further courses in alternative locations are available at http://www.mango-solutions.com/services/training.html More details about this course : - in french : http://www.mango-solutions.com/services/rtraining/r_paris_training_07_french.html - in english : http://www.mango-solutions.com/services/rtraining/r_paris_training_07.html Should you want to book a place on this course or have any questions please contact [EMAIL PROTECTED] Cordialement, Romain Francois -- Mango Solutions Tel +44 1249 467 467 Fax +44 1249 467 468 Mob +44 7813 526 123 data analysis that delivers __ R-help@stat.math.ethz.ch 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] garchFit in R
Dear all, I have problem here : I'm using garchFit from fSeries package, here is part of the script : data - read.table(d:/data.txt) a - garchFit(~garch(1,1),ts(data)) I also attached the file here. In my experience, I got my R not responding. I also tried with a - garchFit(~garch(1,1),ts(data*10)) and it's worked. I wonder if something wrong with the first Thanks __ 0.0026668996 -0.0019157865 -0.0001120967 0.0005845345 0.0003697987 -0.0010323306 -0.0023072483 -0.0005885481 0.0012301371 0.0003082133 -0.0002494891 -0.0002006737 -0.0004800350 -0.0002843525 0.0027182299 -0.0004827581 0.0007702074 -0.0018742761 -0.0012589320 -0.0001864557 0.0019782314 0.00 -0.0016593427 0.0014883173 -0.0019642834 -0.0001129345 0.0003289013 0.0047631296 -0.0003933189 -0.777348 -0.0001992589 -0.0019439182 -0.0017467015 -0.0001716240 -0.0003041862 0.0028812028 -0.0006391600 -0.0004934305 0.0002638840 0.0004931309 0.0002341631 -0.0007321793 -0.0021696036 0.0011669581 -0.0003526987 0.0011745500 -0.0001808695 -0.0006997451 0.587632 0.0011198772 0.0017887369 0.0030052082 0.0012059188 0.0031819752 -0.0032446005 0.0009576615 -0.0030971545 -0.0033876838 0.0007118065 -0.0008289275 -0.0001171526 0.0004440365 -0.0016515719 0.0010317472 -0.0002638158 -0.0009735958 0.0011201799 0.0003223110 -0.0026539675 -0.0005848754 0.0010266956 0.0004805825 -0.0005100232 -0.0012333941 -0.0046007250 -0.0037661601 0.0030195219 0.0011691642 -0.0005518513 0.0012071954 -0.0009286963 -0.0013194775 -0.0010534771 -0.0018384612 0.0010729640 -0.0001352279 -0.0041928562 -0.0048981960 0.0035253602 -0.0007769906 -0.0065450379 0.0003404330 0.0018162840 -0.0008223038 -0.0003036179 -0.0016866227 -0.0038151118 0.0006511983 -0.0049316481 -0.0035685861 0.583904 0.0037786345 0.004192 -0.0019298763 -0.0030373119 -0.0006163457 -0.0058485648 0.0076319879 -0.0061118610 0.0014086934 0.0020437674 0.0014607365 0.0013718807 -0.0041446062 0.0010107937 -0.0025287507 0.0035741117 -0.0003428967 0.0004378049 -0.0009605837 -0.0010898236 0.0020398630 0.0009532263 0.0010508613 -0.0006039345 -0.0034717995 0.0027354396 -0.0039024422 -0.0002178340 0.0013848366 0.0018343314 -0.0003219009 -0.0018887114 0.0018939904 0.0007963918 0.0004529223 0.0008571518 0.0044218012 -0.0019126781 0.0045515451 0.0092559993 -0.0009015621 -0.0020175552 0.0002240705 0.0038168506 -0.0035878071 -0.0002901422 -0.0007389559 0.0051061545 -0.0021933090 0.0014213553 -0.0025780541 -0.0004574410 0.0005336344 -0.0004675298 0.0003608554 0.0007360280 -0.0015191088 -0.0021837991 -0.0047678519 -0.0010459318 0.0033618169 -0.0011022447 0.0011588266 0.0001439934 0.0036812865 -0.0010617579 -0.0018386819 0.0006154677 0.0001178651 -0.0006306943 -0.0001283020 -0.0011409873 -0.0003809962 0.0016194965 0.0001436634 0.0009275365 -0.0017079955 0.0017694197 -0.0006351358 0.153772 -0.358809 -0.0024417258 -0.0006706615 0.0004231532 -0.0003250688 0.00 -0.0013493117 -0.0007721806 -0.0004618912 0.0011615764 -0.0002227404 -0.0010842518 0.0013691318 -0.0006736543 -0.0008721193 0.0036790147 0.0002935971 -0.0001545000 -0.0006959312 -0.0006298763 0.0014236639 0.0016909739 0.0015975386 -0.0005625643 0.0039227325 0.0001673279 -0.0031647730 -0.0008280651 0.0013231273 0.0013343643 -0.0028724331 -0.0002304126 0.0014980535 -0.0012062182 -0.0015279076 0.0022489747 0.0025778462 -0.0014449700 -0.0023558165 -0.0009387271 0.0003644465 0.0052782725 -0.0023175981 -0.0001121273 0.0003362951 -0.916910 -0.0014952546 -0.0008391870 0.0016716533 -0.0013695639 0.0004655229 0.0013630021 -0.0025559437 0.922755 0.0014686387 -0.0004293316 0.0004599820 -0.0009204516 -0.0005327070 0.0016216967 -0.0005620481 0.0013425983 -0.0021153235 0.921851 0.0003224940 0.0012161541 -0.0029080728 0.0004518232 -0.0008167053 -0.0008079421 -0.0032780219 -0.0022896000 0.0021286819 -0.0003479945 -0.0004262835 -0.0013439693 -0.0002400599 0.0019219713 0.0008826071 -0.311203 0.0014344017 0.0003049113 -0.0007031687 0.0014052008 -0.0005419102 0.0033541187 -0.0028844242 -0.103175 0.0012312089 0.0003085428 0.0011550870 -0.0003231148 -0.0015316507 -0.0002626703 0.0018456252 -0.0023353370 -0.0004851011 -0.0008528198 0.0003930220 0.0014243068 -0.0028740447 0.0012842983 -0.0001965414 0.0031186304 -0.0001335643 0.513757 0.0002465190 0.0001745330 -0.0007293975 0.0017341634 -0.0003227070 0.0012945009 0.0042097711 -0.0021506299 0.0039128858 -0.0014132766 -0.0012860343 -0.0001825811 0.0042303056 0.0020048020 -0.0016583125 -0.0024867810 -0.0030701626 -0.0010944863 0.0033814397 -0.0011090121 -0.0015187180 0.0023393556 0.0027394008 -0.0004125788 -0.0007557330 -0.0003985487 -0.0019830371 -0.0001369206 0.0018220686 -0.0002980935 -0.0017877958 0.0012264205 0.0014499989 -0.0018550441 0.0022734809 -0.0001663181 0.0010321589 -0.0008708797 -0.0020962515 0.0022171716 0.0017294980 -0.0001254584 -0.0019265679 0.0009970473 -0.0012189246 0.0022237246 0.0062328191
[R] How to use Rattle for Data mining through R?
Dear Mr. Bengtsson, Now i am able to work with R-Matlab interface comfortably. Thanks to you. Recently, I came to know that R can be used for data mining as well. I went through the following site for this : http://rattle.togaware.com/ As they have suggested, I have also installed the two packages: install.packages(RGtk2) install.packages(rattle) Now, can you explain how to work on this? Can this be used to implement the clustering algorithms? If yes, Kindly elaborate. Bhanu Kalyan K BTech CSE Final Year [EMAIL PROTECTED] Tel :+91-9885238228 __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] query
Hello! I found the ccf function gives different estimates than the simple lag correlations. Why is that? This is my code: set.seed(20) x-rnorm(20) y-x+rnorm(20,sd=0.3) print(R CCF:) print(ccf(x,y,lag.max=2,plot=F)) myccf- c( cor(y[-(1:2)],x[-(19:20)]) , cor(y[-1],x[-20]), cor(y,x), cor(x[-1],y[-20]),cor(x[-(1:2)],y[-(19:20)]) ) print(My CCF:) print(myccf) Thank You! Ron [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] scripts with littler
[John Lawrence Aspden] I'm trying to write R scripts using littler (under Debian), and was originally using the shebang line: #!/usr/bin/env r However this picks up any .RData file that happens to be lying around, which I find a little disturbing, because it means that the script may not behave the same way on successive invocations. If you drop the /usr/bin/env trick then #!/usr/bin/r --vanilla seems to work, but it also prevents the loading of the libraries in my home directory, some of which I'd like to use. #!/usr/bin/r --no-restore doesn't work at all. Ideally I'd like #!/usr/bin/env r --no-restore Has anyone else been round this loop and can offer advice? I usually do something like: #!/bin/sh R --slave --vanilla EOF R script goes here... EOF # vim: ft=r If you need to search special places for packages, you may tweak exported environment variables between the first and second line. -- François Pinard http://pinard.progiciels-bpi.ca __ R-help@stat.math.ethz.ch 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] scripts with littler / subroutines
[John Lawrence Aspden] Another difficulty I'm having is creating a common function (foo, say) to share between two scripts. In your previous message, you were telling us that you want to load from your home directory. You might put the common functions there, maybe? -- François Pinard http://pinard.progiciels-bpi.ca __ R-help@stat.math.ethz.ch 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] garchFit in R
See ?garchFit . The data argument is supposed to be of class timeSeries or a data frame, not of class ts. Furthermore even if it did accept a variable of class ts the ts function does not take a data frame as its argument. See ?ts Follow the examples of using garchFit here: https://svn.r-project.org/Rmetrics/trunk/fSeries/test/runit4C.R and also review all your code doing a ? on each function that you use, performing a class(x) on each argument, x, ensuring that each function is called with the variables of the appropriate class. On 1/6/07, Melina Chen [EMAIL PROTECTED] wrote: Dear all, I have problem here : I'm using garchFit from fSeries package, here is part of the script : data - read.table(d:/data.txt) a - garchFit(~garch(1,1),ts(data)) I also attached the file here. In my experience, I got my R not responding. I also tried with a - garchFit(~garch(1,1),ts(data*10)) and it's worked. I wonder if something wrong with the first Thanks __ 0.0026668996 -0.0019157865 -0.0001120967 0.0005845345 0.0003697987 -0.0010323306 -0.0023072483 -0.0005885481 0.0012301371 0.0003082133 -0.0002494891 -0.0002006737 -0.0004800350 -0.0002843525 0.0027182299 -0.0004827581 0.0007702074 -0.0018742761 -0.0012589320 -0.0001864557 0.0019782314 0.00 -0.0016593427 0.0014883173 -0.0019642834 -0.0001129345 0.0003289013 0.0047631296 -0.0003933189 -0.777348 -0.0001992589 -0.0019439182 -0.0017467015 -0.0001716240 -0.0003041862 0.0028812028 -0.0006391600 -0.0004934305 0.0002638840 0.0004931309 0.0002341631 -0.0007321793 -0.0021696036 0.0011669581 -0.0003526987 0.0011745500 -0.0001808695 -0.0006997451 0.587632 0.0011198772 0.0017887369 0.0030052082 0.0012059188 0.0031819752 -0.0032446005 0.0009576615 -0.0030971545 -0.0033876838 0.0007118065 -0.0008289275 -0.0001171526 0.0004440365 -0.0016515719 0.0010317472 -0.0002638158 -0.0009735958 0.0011201799 0.0003223110 -0.0026539675 -0.0005848754 0.0010266956 0.0004805825 -0.0005100232 -0.0012333941 -0.0046007250 -0.0037661601 0.0030195219 0.0011691642 -0.0005518513 0.0012071954 -0.0009286963 -0.0013194775 -0.0010534771 -0.0018384612 0.0010729640 -0.0001352279 -0.0041928562 -0.0048981960 0.0035253602 -0.0007769906 -0.0065450379 0.0003404330 0.0018162840 -0.0008223038 -0.0003036179 -0.0016866227 -0.0038151118 0.0006511983 -0.0049316481 -0.0035685861 0.583904 0.0037786345 0.004192 -0.0019298763 -0.0030373119 -0.0006163457 -0.0058485648 0.0076319879 -0.0061118610 0.0014086934 0.0020437674 0.0014607365 0.0013718807 -0.0041446062 0.0010107937 -0.0025287507 0.0035741117 -0.0003428967 0.0004378049 -0.0009605837 -0.0010898236 0.0020398630 0.0009532263 0.0010508613 -0.0006039345 -0.0034717995 0.0027354396 -0.0039024422 -0.0002178340 0.0013848366 0.0018343314 -0.0003219009 -0.0018887114 0.0018939904 0.0007963918 0.0004529223 0.0008571518 0.0044218012 -0.0019126781 0.0045515451 0.0092559993 -0.0009015621 -0.0020175552 0.0002240705 0.0038168506 -0.0035878071 -0.0002901422 -0.0007389559 0.0051061545 -0.0021933090 0.0014213553 -0.0025780541 -0.0004574410 0.0005336344 -0.0004675298 0.0003608554 0.0007360280 -0.0015191088 -0.0021837991 -0.0047678519 -0.0010459318 0.0033618169 -0.0011022447 0.0011588266 0.0001439934 0.0036812865 -0.0010617579 -0.0018386819 0.0006154677 0.0001178651 -0.0006306943 -0.0001283020 -0.0011409873 -0.0003809962 0.0016194965 0.0001436634 0.0009275365 -0.0017079955 0.0017694197 -0.0006351358 0.153772 -0.358809 -0.0024417258 -0.0006706615 0.0004231532 -0.0003250688 0.00 -0.0013493117 -0.0007721806 -0.0004618912 0.0011615764 -0.0002227404 -0.0010842518 0.0013691318 -0.0006736543 -0.0008721193 0.0036790147 0.0002935971 -0.0001545000 -0.0006959312 -0.0006298763 0.0014236639 0.0016909739 0.0015975386 -0.0005625643 0.0039227325 0.0001673279 -0.0031647730 -0.0008280651 0.0013231273 0.0013343643 -0.0028724331 -0.0002304126 0.0014980535 -0.0012062182 -0.0015279076 0.0022489747 0.0025778462 -0.0014449700 -0.0023558165 -0.0009387271 0.0003644465 0.0052782725 -0.0023175981 -0.0001121273 0.0003362951 -0.916910 -0.0014952546 -0.0008391870 0.0016716533 -0.0013695639 0.0004655229 0.0013630021 -0.0025559437 0.922755 0.0014686387 -0.0004293316 0.0004599820 -0.0009204516 -0.0005327070 0.0016216967 -0.0005620481 0.0013425983 -0.0021153235 0.921851 0.0003224940 0.0012161541 -0.0029080728 0.0004518232 -0.0008167053 -0.0008079421 -0.0032780219 -0.0022896000 0.0021286819 -0.0003479945 -0.0004262835 -0.0013439693 -0.0002400599 0.0019219713 0.0008826071 -0.311203 0.0014344017 0.0003049113 -0.0007031687 0.0014052008 -0.0005419102 0.0033541187 -0.0028844242 -0.103175 0.0012312089 0.0003085428
Re: [R] scripts with littler
Thanks, that's a really neat mechanism, ( I especially like the note to vim, which will save all my scripts having to end .R ) Is there any way to get at the command line and stdio though? With littler I can do things like: #!/usr/bin/env r print(argv) t=read.table(file=stdin()) so that I can write unix-style filters. Cheers, John. François Pinard wrote: I usually do something like: #!/bin/sh R --slave --vanilla EOF R script goes here... EOF # vim: ft=r If you need to search special places for packages, you may tweak exported environment variables between the first and second line. -- Contractor in Cambridge UK -- http://www.aspden.com __ R-help@stat.math.ethz.ch 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] scripts with littler / subroutines
François Pinard wrote: [John Lawrence Aspden] Another difficulty I'm having is creating a common function (foo, say) to share between two scripts. In your previous message, you were telling us that you want to load from your home directory. You might put the common functions there, maybe? I am doing at the moment, and using source to load them in. I'm worried about what happens when I come to distribute the code though. After a couple of e-mails off-list (thanks Dirk!) it sounds as though the solution is to create a library for R with the common subroutines in, and then load that from the scripts. Cheers, John. -- Contractor in Cambridge UK -- http://www.aspden.com __ R-help@stat.math.ethz.ch 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] scripts with littler
Looks like it will be possible to write scripts with R 2.5.0 using the new -f flag and file(stdin). From https://svn.r-project.org/R/trunk/NEWS : o Command-line R (and Rterm.exe under Windows) accepts the options '-f filename', '--file=filename' and '-e expression' to follow other script interpreters. These imply --no-save unless --save is specified. [..] o file(stdin) is now recognized, and refers to the process's 'stdin' file stream whereas stdin() refers to the console. These may differ, for example for a GUI console, an embedded application of R or if --file= has been used. On 1/8/07, John Lawrence Aspden [EMAIL PROTECTED] wrote: Thanks, that's a really neat mechanism, ( I especially like the note to vim, which will save all my scripts having to end .R ) Is there any way to get at the command line and stdio though? With littler I can do things like: #!/usr/bin/env r print(argv) t=read.table(file=stdin()) so that I can write unix-style filters. Cheers, John. François Pinard wrote: I usually do something like: #!/bin/sh R --slave --vanilla EOF R script goes here... EOF # vim: ft=r If you need to search special places for packages, you may tweak exported environment variables between the first and second line. -- Contractor in Cambridge UK -- http://www.aspden.com __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Course announcement: STATISTICAL PRACTICE IN EPIDEMIOLOGY USING R
Course in STATISTICAL PRACTICE IN EPIDEMIOLOGY USING R Tartu, Estonia, 25 to 30 May 2007 The course is aimed at epidemiologists and statisticians who wish to use R for statistical modelling and analysis of epidemiological data. The course requires basic knowledge of epidemiological concepts and study types. These will only be briefly reviewed, whereas the more advanced epidemiological and statistical concepts will be treated in depth. Contents: - * History of R. Language. Objects. Functions. * Interface to other dataformats. Dataframes. * Graphical methods for exploring data. * Classical methods and tabulation of data. * Logistic regression for case-control-studies. * Poisson regression for follow-up studies. * Parametrization of models. * Graphics in R. * Graphical reporting of results. * Causal inference. * Time-splitting SMR. * Survival analysis in continuous time. * Interval censoring. * Nested and matched case-control studies. * Case-cohort studies. * Competing risk models. * Multistage models. * Bootstrap and simulation The methods will be illustrated using R in practical exercises. The Epi package which is under development for epidemiological analysis in R will be introduced. Participants are required to have a fairly good understanding of statistical principles and some familiarity with epidemiological concepts. The course will be mainly practically oriented with more than half the time at the computer. Price: 600 EUR. (300 EUR for countries outside EU-2003 and the like). Application: Deadline 1st April 2007. Send and e-mail which briefly states your qualifications in epidemiology and statistics, to the organizers Krista Fischer, Esa Läärä Bendix Carstensen. Further information at: www.pubhealth.ku.dk/~bxc/SPE --- Organizers: Krista Fischer, University of Tartu, Estonia [EMAIL PROTECTED] Esa Läärä, University of Oulu, Finland [EMAIL PROTECTED] Bendix Carstensen, Steno Diabetes Center, Denmark [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch 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] memory problem
On Sat, 6 Jan 2007, Zoltan Kmetty wrote: Hi! I had some memory problem with R - hope somebody could tell me a solution. I work with very large datasets, but R cannot allocate enough memoty to handle these datasets. You haven't said what you want to do with these datasets. -thomas __ R-help@stat.math.ethz.ch 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] limitation in the number of covariates in nlme
Dear All I am fitting a nlme model in which I have 7 covariates. Adding one more variable to the model, R gives me an error message: Error in parse(file, n, text, prompt) : syntax error in list( .. This does not depend on which variables are in the model and seems to depend strictly on the number of covariates. Any suggestion would be appreciated. M.Fararooei PhD candidate __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] fSeries Package
Dear All; I have used fbmSim to simulate a fbm sequence, however, when I tried to estimate the Hurst effect, none of the nine procedures gave me an answer close enough to the real value, which is 0.5 (n=1000). So, would you please advice, 1. which is the best method to estimate the H among the 9 mehods, R/S, higuchi or Whittle? 2. how to choose the levels (default=50), minnpts, cutoff values or if there is any other issues to consider? Would you please send your code if you can get the right estimate for the attached dataset? 3. I also simulated multiple sequences, but some of the estimated results have H1, how would you explain this, and how to correct it. 4. if I have a sample size of 30, what are your suggestions for estimating the hurst effect. I really appreciate your help, and thanks in advance. Sincerely; Ed [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] fSeries Package
Dear All; I have used fbmSim to simulate a fbm sequence, however, when I tried to estimate the Hurst effect, none of the nine procedures gave me an answer close enough to the real value, which is 0.5 (n=1000). So, would you please advice, 1. which is the best method to estimate the H among the 9 mehods, R/S, higuchi or Whittle? 2. how to choose the levels (default=50), minnpts, cutoff values or if there is any other issues to consider? Would you please send your code if you can get the right estimate for the attached dataset? 3. I also simulated multiple sequences, but some of the estimated results have H1, how would you explain this, and how to correct it. 4. if I have a sample size of 30, what are your suggestions for estimating the hurst effect. I really appreciate your help, and thanks in advance. Sincerely; Qing list(c(0, 0.0602883614054335, 0.0792551804556156, 0.109563140496959, 0.125726475390261, 0.101877497256596, 0.0571926667502657, 0.00262554012667387, -0.0651825041744684, -0.0696503406796901, -0.0688337926741136, -0.0361989921035026, -0.0496524166395568, -0.0718218507093852, -0.109583486993751, -0.0451891749832022, -0.0260755094163026, -0.0201228029445018, -0.08818052945358, -0.0285680272562049, -0.032752629105123, -0.00199553309054604, 0.00508312076775159, -0.0382257524810562, -0.0398084284989033, -0.0502088451482971, -0.0502183047870017, -0.0174725900800023, -0.031457396692228, -0.0497298422601627, -0.0499422794745919, -0.0361646489128442, 0.0266653302426084, -0.00219111075589404, 0.0200305010061950, -0.054431205284715, -0.00789973517059908, -0.0085425214867059, -0.0541809440614641, -0.110006586793787, -0.127781398474619, -0.149159749479771, -0.0888724748560444, -0.0768016585462973, -0.0427333724364433, -0.0562443902614682, -0.062866380084345, -0.0883889349587378, -0.08412713827269, -0.124694662643563, - 0.0692092347299578, -0.062046981143375, -0.0853376756560203, -0.0994827776216755, -0.0599248702862878, -0.086369926350214, -0.0890587510305954, -0.0599052704934926, -0.0393644348210234, -0.0364342257334110, -0.0352152731793845, 0.00857219866032972, 0.0180050537574112, -0.0356947245542089, -0.0615077884110117, -0.0650043906408892, -0.0357502728853327, 0.00485292461594026, -0.0458490824792766, -0.0735087346178546, -0.0820482814570969, -0.124917946967105, -0.102342757999288, -0.154497291254316, -0.181381845540350, - 0.166583783090691, -0.130709738638527, -0.124693013403996, -0.120174007595549, - 0.204900741024172, -0.187508161990262, -0.200032164010717, -0.224311714556569, - 0.207979212824500, -0.232450923263701, -0.198989498760939, -0.215501785889735, - 0.226880158415004, -0.203545247216445, -0.182379290331033, -0.197038481353429, - 0.183796217531869, -0.215299419717715, -0.226095790998872, -0.201080854888686, - 0.261516787028393, -0.228388047078831, -0.233878235687051, -0.250375640774054, - 0.245746001611628, -0.232938343176222, -0.204702689747725, -0.259350393091606, - 0.266266298423241, -0.261596784773769, -0.259875864886204, -0.288719457448324, - 0.318140871065267, -0.304593775001704, -0.263467947228369, -0.323808258544402, - 0.368149351192211, -0.347335883864181, -0.400024671714471, -0.371544405921674, - 0.34497157633729, -0.418657437186672, -0.446912741927435, -0.443280747761798, - 0.384739689692638, -0.408072099289829, -0.44994167683647, -0.495273953054503, - 0.495799924479583, -0.43697383254148, -0.440650597876129, -0.458929575025839, - 0.464585181026337, -0.455843249117235, -0.505571057794026, -0.528316203388037, - 0.58236723395483, -0.519865988395428, -0.555187599676786, -0.532496699903787, - 0.522718022822901, -0.559598211031558, -0.54708053308, -0.554634133071482, - 0.541090495738355, -0.558915651522986, -0.541917600099341, -0.578140869146858, - 0.53827826166188, -0.52995892714492, -0.502706986562639, -0.497002923985933, - 0.488096453915811, -0.51306171001298, -0.536938942207764, -0.515525690037527, - 0.527192086185579, -0.511195825348352, -0.531104487863626, -0.521038783472886, - 0.519956505596612, -0.510535242028159, -0.531234776730198, -0.526733559471536, - 0.583555032968273, -0.551226199377139, -0.489093347568197, -0.505836247919194, - 0.485420121220644, -0.511258369655571, -0.505044073824655, -0.496646898991666, - 0.49767793016268, -0.496864531091594, -0.545965735276333, -0.588151447068976, - 0.594481697088302, -0.633356216248837, -0.649947987535778, -0.698052359479746, - 0.651147537552288, -0.678918599568793, -0.707817506128165, -0.69962378236799, - 0.664061266573256, -0.686809968963275, -0.70940931290113, -0.710042179498104, - 0.700294406700751, -0.69089796594532, -0.687411073827526, -0.660740247977237, -0.61857834066703, -0.611492191585365, -0.617870447722936, -0.590305790642949, - 0.616713901938279, -0.619126236382548, -0.618591413756597, -0.604886044395737, - 0.598434945889939, -0.481524771809731, -0.424388823122359, -0.490492676413456, - 0.506402791875861, -0.480172973435785, -0.517922095978117, -0.502318428525046, - 0.496731810144271, -0.531408048623419,
[R] Simple spectral analysis
Hello world, I am actually trying to transfer a lecture from Statistica to R and I ran into problems with spectral analysis, I think I just don't get it 8-( (The posting from FFT, frequs, magnitudes, phases from 2005 did not enlighten me) As a starter for the students I have a 10year data set of air temperature with daily values and I try to get a periodogram where the annual period (365 days) should be clearly visible (in statistica I can get the frequencies and the period). I tried the spectrum() and pgram() functions, but did not find a way through... The final aim would be to get the periodogram (and the residuals from the reassembled data set...) Thanks and greetings, Georg The data set: air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) airtemp = ts(T_air, start=c(1989,1), freq = 365) plot(airtemp) -- Georg Hoermann, Dep. of Hydrology, Ecology, Kiel University, Germany +49/431/23761412, mo: +49/171/4995884, icq:348340729, skype: ghoermann __ R-help@stat.math.ethz.ch 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] OLS in S+
Dear all, Is there any equivalent of the function OLS in S+ in R? Thanks and regards, megh __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] Access, Process and Read Information from Web Sites
Dear R useRs, Does any of you know if it is possible to access a web site (e.g., www.marriott.com), fill in the requested information (e.g., city, check-in date, etc), and save the results (e.g., room availability and room rates) in text files through R? I started with url and url.show but it seems that this does not do what I would like to do. Any lead would be greatly appreciated. Thanks. Tudor -- Tudor Dan Bodea Ph.D. Candidate Georgia Institute of Technology School of Civil and Environmental Engineering __ R-help@stat.math.ethz.ch 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] limitation in the number of covariates in nlme
Please check you have the latest version of nlme (3.1-79), as some restrictions of this sort were lifted a few weeks ago. If you have, please note the advice about a minimal reproducible example in the footer of every help message as we will need one to be able to help you. On Mon, 8 Jan 2007, mohammad frarouei wrote: Dear All I am fitting a nlme model in which I have 7 covariates. Adding one more variable to the model, R gives me an error message: Error in parse(file, n, text, prompt) : syntax error in list( .. This does not depend on which variables are in the model and seems to depend strictly on the number of covariates. Any suggestion would be appreciated. M.Fararooei PhD candidate __ [[alternative HTML version deleted]] -- 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__ R-help@stat.math.ethz.ch 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] OLS in S+
Megh Dal wrote: Dear all, Is there any equivalent of the function OLS in S+ in R? Thanks and regards, megh If you are asking about the ols function in the Design library, it's in the Design package in R. ols is a wrapper for lm that makes certain plots and penalized estimations easier to do. Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University __ R-help@stat.math.ethz.ch 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] Cross-compilation of R and ld bug ?
Hello list, I would like to cross-compile R packages using R 2.4.0. I am working on Linux Debian and cross-compiled (windows binaries) without problems with older R version. I have used the doc of Yan and Rossini in the contributed section of the R documentation (same version of MinGW...). When I try to cross-compile R (make R), the procedure stopped and returns : i586-mingw32-windres --include-dir ../include -i dllversion.rc -o dllversion.o i586-mingw32-gcc -shared -s -mwindows -o R.dll R.def console.o dataentry.o dynl oad.o edit.o editor.o embeddedR.o extra.o opt.o pager.o preferences.o psignal.o rhome.o rui.o run.o shext.o sys-win32.o system.o e_pow.o malloc.o ../main/libmai n.a ../appl/libappl.a ../nmath/libnmath.a graphapp/ga.a getline/gl.a ../extra/xd r/libxdr.a ../extra/zlib/libz.a ../extra/pcre/libpcre.a ../extra/bzip2/libbz2.a ../extra/intl/libintl.a ../extra/trio/libtrio.a dllversion.o -L. -lg2c -lRblas - lcomctl32 -lversion ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1703): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1740): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1848): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x187f): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1966): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1f2a): more un defined references to `__pcre_ucp_findprop' follow collect2: ld returned 1 exit status make[4]: *** [R.dll] Erreur 1 make[3]: *** [../../bin/R.dll] Erreur 2 make[2]: *** [rbuild] Erreur 2 make[1]: *** [all] Erreur 2 make[1]: quittant le répertoire « /home/stephane/Rdev/CrossCompileBuild/WinR/R-2 .4.0/src/gnuwin32 » I have read (http://www.murdoch-sutherland.com/Rtools/) that a bug exists for ld version 2.16.91 20050827 and that Prof Ripley produced a patched version. It seems that my problem is also related to ld (and I have the same version). So I wonder if the same bug could be responsible of the error in the cross-compiler. Two questions: - Are they other people which have the same problem when cross-compiling R on Linux - Is it possible that the problem is related to ld. If yes, is it possible to obtain a patched version ? Thanks in advance. Sincerely, -- Stéphane DRAY ([EMAIL PROTECTED] ) Laboratoire BBE-CNRS-UMR-5558, Univ. C. Bernard - Lyon I 43, Bd du 11 Novembre 1918, 69622 Villeurbanne Cedex, France Tel: 33 4 72 43 27 57 Fax: 33 4 72 43 13 88 http://biomserv.univ-lyon1.fr/~dray/ __ R-help@stat.math.ethz.ch 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] Boxplot issue
Dear R-users, I have a data frame containing 2 colums: column 1 is the patient numbers (totally 36 patients), column 2 is patient's response values (each patient has 100 response values). If I produce a boxplot for each patient on the same graph in order to compare them against each other then the boxplots are very small. How can I instead of creating one graph containing 36 boxplots, create four different graphs where three of them have 10 boxplots each representing data of 10 patients and the fourth graph has boxplots of remaining patients ? Thanks alot for any suggestion, Greetings, Antonia __ R-help@stat.math.ethz.ch 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] Cross-compilation of R and ld bug ?
There are two problems here: 1) your binutils is not current. 2) your R is not current. Updating either will solve this, but please update both. Almost up-to-date cross-compilers are (as ever) available from http://www.stats.ox.ac.uk/pub/Rtools/ (If you want to compile R-devel you will need to update the mingw, which can be done from the i386 distribution. I will rebuild the cross-compilers in due course.) On Mon, 8 Jan 2007, Stéphane Dray wrote: Hello list, I would like to cross-compile R packages using R 2.4.0. I am working on Linux Debian and cross-compiled (windows binaries) without problems with older R version. I have used the doc of Yan and Rossini in the contributed section of the R documentation (same version of MinGW...). When I try to cross-compile R (make R), the procedure stopped and returns : i586-mingw32-windres --include-dir ../include -i dllversion.rc -o dllversion.o i586-mingw32-gcc -shared -s -mwindows -o R.dll R.def console.o dataentry.o dynl oad.o edit.o editor.o embeddedR.o extra.o opt.o pager.o preferences.o psignal.o rhome.o rui.o run.o shext.o sys-win32.o system.o e_pow.o malloc.o ../main/libmai n.a ../appl/libappl.a ../nmath/libnmath.a graphapp/ga.a getline/gl.a ../extra/xd r/libxdr.a ../extra/zlib/libz.a ../extra/pcre/libpcre.a ../extra/bzip2/libbz2.a ../extra/intl/libintl.a ../extra/trio/libtrio.a dllversion.o -L. -lg2c -lRblas - lcomctl32 -lversion ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1703): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1740): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1848): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x187f): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1966): undefin ed reference to `__pcre_ucp_findprop' ../extra/pcre/libpcre.a(pcre_dfa_exec.o):pcre_dfa_exec.c:(.text+0x1f2a): more un defined references to `__pcre_ucp_findprop' follow collect2: ld returned 1 exit status make[4]: *** [R.dll] Erreur 1 make[3]: *** [../../bin/R.dll] Erreur 2 make[2]: *** [rbuild] Erreur 2 make[1]: *** [all] Erreur 2 make[1]: quittant le répertoire « /home/stephane/Rdev/CrossCompileBuild/WinR/R-2 .4.0/src/gnuwin32 » I have read (http://www.murdoch-sutherland.com/Rtools/) that a bug exists for ld version 2.16.91 20050827 and that Prof Ripley produced a patched version. It seems that my problem is also related to ld (and I have the same version). So I wonder if the same bug could be responsible of the error in the cross-compiler. Two questions: - Are they other people which have the same problem when cross-compiling R on Linux - Is it possible that the problem is related to ld. If yes, is it possible to obtain a patched version ? Thanks in advance. Sincerely, -- 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__ R-help@stat.math.ethz.ch 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] Boxplot issue
How about 4 plots of 9 each. You can change the 'cut' for other distributions of your IDs. pData - data.frame(id=sample(1:36,1000,T), data=rnorm(1000)) # sample data partData - split(pData, cut(pData$id, 4)) # split into 4 groups boxplot(data ~ id, pData) # original plot lapply(partData, function(x) boxplot(data ~ id, x)) # 4 plots On 1/8/07, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote: Dear R-users, I have a data frame containing 2 colums: column 1 is the patient numbers (totally 36 patients), column 2 is patient's response values (each patient has 100 response values). If I produce a boxplot for each patient on the same graph in order to compare them against each other then the boxplots are very small. How can I instead of creating one graph containing 36 boxplots, create four different graphs where three of them have 10 boxplots each representing data of 10 patients and the fourth graph has boxplots of remaining patients ? Thanks alot for any suggestion, Greetings, Antonia __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] memory problem --- use sparse matrices
UweL == Uwe Ligges [EMAIL PROTECTED]
on Sun, 07 Jan 2007 09:42:08 +0100 writes:
UweL Zoltan Kmetty wrote:
Hi!
I had some memory problem with R - hope somebody could
tell me a solution.
I work with very large datasets, but R cannot allocate
enough memoty to handle these datasets.
I want work a matrix with row= 100 000 000 and column=10
A know this is 1 milliard cases, but i thought R could
handle it (other commercial software like spss could do),
but R wrote out everytime: not enough memory..
any good idea?
UweL Buy a machine that has at least 8Gb (better 16Gb) of
UweL RAM and proceed ...
Well, I doubt that Zoltan wants to *fill* his matrix with all
non-zeros. If he does, Uwe and Roger are right.
Otherwise, working with a *sparse* matrix, using the 'Matrix'
(my recommendation, but I am biased) or 'SparseM' package, might
well be feasible:
install.packages(Matrix) # if needed; only once for your R
library(Matrix) # each time you need it
TsparseMatrix - function(nrow, ncol, i,j,x)
{
## Purpose: User friendly construction of sparse Matrix from triple
## --
## Arguments: (i,j,x): 2 integer and 1 numeric vector of the same length:
##
## The matrix M will have
## M[i[k], j[k]] == x[k] , for k = 1,2,..., length(i)
##and M[ i', j' ] == 0 for `` all other pairs (i',j')
## --
## Author: Martin Maechler, Date: 8 Jan 2007, 18:46
nnz - length(i)
stopifnot(length(j) == nnz, length(x) == nnz,
is.numeric(x), is.numeric(i), is.numeric(j))
dim - c(as.integer(nrow), as.integer(ncol))
## The conformability of (i,j) with 'dim' will be checked automatically
## by an internal validObject() that is part of new(.):
new(dgTMatrix, x = x, Dim = dim,
## our Tsparse Matrices use 0-based indices :
i = as.integer(i - 1:1),
j = as.integer(j - 1:1))
}
For example :
TsparseMatrix(10,20, c(1,3:8), c(2,9,6:10), 7 * (1:7))
10 x 20 sparse Matrix of class dgTMatrix
[1,] . 7 . . . . . . . . . . . . . . . . . .
[2,] . . . . . . . . . . . . . . . . . . . .
[3,] . . . . . . . . 14 . . . . . . . . . . .
[4,] . . . . . 21 . . . . . . . . . . . . . .
[5,] . . . . . . 28 . . . . . . . . . . . . .
[6,] . . . . . . . 35 . . . . . . . . . . . .
[7,] . . . . . . . . 42 . . . . . . . . . . .
[8,] . . . . . . . . . 49 . . . . . . . . . .
[9,] . . . . . . . . . . . . . . . . . . . .
[10,] . . . . . . . . . . . . . . . . . . . .
But
nr - 1e8
nc - 10
set.seed(1)
i - sample(nr, 1)
j - sample(nc, 1)
x - round(rnorm(1), 2)
M - TsparseMatrix(nr, nc, i=i, j=j, x=x)
works,
e.g. you can
x - 1:10
system.time(y - M %*% x) # needs around 4 sec on one of our better machines
y - as.vector(y)
## but you can become even more efficient, translating from the
## so-called triplet to the (recommended) Csparse
## representation:
M. - as(M, CsparseMatrix)
object.size(M) / object.size(M.)
## 1.328921; i.e. we saved 33%
## and
system.time(y. - M. %*% x) # much faster (1 sec)
identical(as.vector(y.), y)
--- --- ---
I hope this is useful to you.
Martin Maechler,
ETH Zurich
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Re: [R] Plot .jpeg image in margins?
Here is one example of a way to do it: library(rimage) # for the read.jpeg function library(TeachingDemos) # for the subplot function par(xpd=NA,mar=c(5,4,4,8)+0.1) plot(1:10,10:1) x - read.jpeg(system.file(data, cat.jpg, package=rimage)) subplot( plot(x), 12, 5 ) Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Kari Sent: Sunday, January 07, 2007 10:10 PM To: r-help@stat.math.ethz.ch Subject: [R] Plot .jpeg image in margins? Is it possible to plot an image (currently a jpeg) in the margins? Thanks, Kari [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] odfWeave and figures in MS Word Format
I answer to myself. I understood my error : first of all, we have to save the file in the .rtf format ! Then, from the rtf file, we can generate the file in the .doc format. I am sorry for my question. Thanks Laurent __ R-help@stat.math.ethz.ch 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] query
Look at : myccf * c(17,18,19,18,17)/19 Do those numbers match with the result of ccf? -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Fluss Sent: Monday, January 08, 2007 6:18 AM To: r-help@stat.math.ethz.ch Subject: [R] query Hello! I found the ccf function gives different estimates than the simple lag correlations. Why is that? This is my code: set.seed(20) x-rnorm(20) y-x+rnorm(20,sd=0.3) print(R CCF:) print(ccf(x,y,lag.max=2,plot=F)) myccf- c( cor(y[-(1:2)],x[-(19:20)]) , cor(y[-1],x[-20]), cor(y,x), cor(x[-1],y[-20]),cor(x[-(1:2)],y[-(19:20)]) ) print(My CCF:) print(myccf) Thank You! Ron [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] coefficients of each local polynomial from loess() or locfit()
Dieter, Thanks for your suggestions and help. I am not an expert with R programming. In my current application, I am not interested in point prediction from loess(). Instead, I am more interested in obtaining the coefficient estimates of local polynomial from loess(). Is it straightforward to modify loess() so that the coefficient estimates can be put into the return list of loess()? Delong -- Message: 8 Date: Fri, 5 Jan 2007 14:01:46 + (UTC) From: Dieter Menne [EMAIL PROTECTED] Subject: Re: [R] coefficients of each local polynomial from loess() or locfit() To: r-help@stat.math.ethz.ch Message-ID: [EMAIL PROTECTED] Content-Type: text/plain; charset=us-ascii Liu, Delong (NIH/CIT) [C] liud2 at mail.nih.gov writes: I want to extract estimated coeffiicents of each local polynomial at given x from loess(), locfit(), or KernSmooth(). Can some experts provide me with suggestions? Thanks. Try cars.lo - loess(dist ~ speed, cars) str(cars.lo) List of 17 $ n: int 50 $ fitted : num [1:50] 5.89 5.89 12.57 12.57 15.37 ... $ residuals: Named num [1:50] -3.894 4.106 -8.568 9.432 0.631 ... ... omitted ..$ cell : num 0.2 ..$ family : chr gaussian ..$ iterations : num 1 $ kd :List of 5 ..$ parameter: Named int [1:7] 1 50 2 19 11 1049 849 .. ..- attr(*, names)= chr [1:7] d n vc nc ... ..$ a: int [1:19] 1 1 1 1 1 1 1 0 0 0 ... ..$ xi : num [1:19] 15 12 19 9 13 17 20 0 0 0 ... ..$ vert : num [1:2] 3.90 25.11 ..$ vval : num [1:22] 5.71 1.72 96.46 10.88 41.21 ... $ call : language loess(formula = dist ~ speed, data = cars) Looks like kd holds information about the polynomials. Then, try getAnywhere(predict.loess) which will show you that the real work is done in function predLoess. Trying again getAnywhere(predLoess) you get an idea how the parameters are used for prediction. fit[inside] - .C(R_loess_ifit, as.integer(kd$parameter), as.integer(kd$a), as.double(kd$xi), as.double(kd$vert), as.double(kd$vval), as.integer(M1), as.double(x.evaluate[inside, ]), fit = double(M1))$fit Dieter __ R-help@stat.math.ethz.ch 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] Ecartis command results: -- Binary/unsupported file stripped by Ecartis --
Request received for list 'unicode' via request address. The original message was received at Mon, 8 Jan 2007 21:05:47 +0200 from 2.178.6.230 Unknown command. - The following addresses had permanent fatal errors - Unknown command. [EMAIL PROTECTED] Unknown command. --- Ecartis v1.0.0 - job execution complete. __ R-help@stat.math.ethz.ch 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] spatio temporal plot
Dear R-users, I have a matrix of data (air pollution) with n rows and T columns, where n is the number of spatial locations and T is the number of time points (days of the year). I would like to use a 3d plot for plotting the n time series I have: so x-axis and y-axis are for the spatial coordinates and the z-axis is for the T air pollution data. But the final result should be like this: see the attached figure. It's like doing n vertical plots of the n time series and put them nearby using the spatial coordinates. Can you help me please? Thanks in advance, best regards Michela timeseriesplot.PNG Description: PNG image __ R-help@stat.math.ethz.ch 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] coefficients of each local polynomial from loess() or locfit()
Liu, Delong (NIH/CIT) [C] liud2 at mail.nih.gov writes: Instead, I am more interested in obtaining the coefficient estimates of local polynomial from loess(). Is it straightforward to modify loess() so that the coefficient estimates can be put into the return list of loess()? No need to change loess. cars.lo - loess(dist ~ speed, cars) str(cars.lo) List of 17 ... $ kd :List of 5 ..$ parameter: Named int [1:7] 1 50 2 19 11 1049 849 .. ..- attr(*, names)= chr [1:7] d n vc nc ... ..$ a: int [1:19] 1 1 1 1 1 1 1 0 0 0 ... ..$ xi : num [1:19] 15 12 19 9 13 17 20 0 0 0 ... ..$ vert : num [1:2] 3.90 25.11 ..$ vval : num [1:22] 5.71 1.72 96.46 10.88 41.21 ... As I showed you, they are in cars.lo$kd, but you must dig into the source code to find out how they are used. And after reading Brian Ripley's warning, I would recommend that you don't try it if you are not sure how extract these. Dieter __ R-help@stat.math.ethz.ch 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] finer control of scales in xyplot
When plotting over multiple pages in lattice, I'd like to be able to have same scales within a page, but free scales between pages. In other words, something like: z-data.frame(x=1:100, y=runif(100), d=rep(1:2,50), p=rep(1:2,each=50)) plot-xyplot(y~x|d*p, data=z, scales=list(x=list(relation=free)), layout=c(1,2)) but within a page, to have common x-axes. As long as 'x' is sorted, I can get the desired effect by transforming x to a relative scale: plot-xyplot(y~unlist(with(z,tapply(x,p,function(x) (x-min(x))/diff(range(x)|d*p, data=z, layout=c(1,2)) except that I'd like the tickmark labels to be in the original units of 'x'. I've started looking at xscale.components.default to see whether it can work on a per-page (instead of per-panel) basis, but I get the nagging suspicion that I'm making this harder than it needs to be. Any assistance greatly appreciated. Thanks, Ben __ R-help@stat.math.ethz.ch 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] spatio temporal plot
Altough I didn't test it, I think rgl package should do this. Regards, Scionforbai __ R-help@stat.math.ethz.ch 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] listing all functions in R
Prof Brian Ripley [EMAIL PROTECTED] wrote in message
news:[EMAIL PROTECTED]
Here is a reasonable shot:
findfuns - function(x) {
if(require(x, character.only=TRUE)) {
env - paste(package, x, sep=:)
nm - ls(env, all=TRUE)
nm[unlist(lapply(nm, function(n) exists(n, where=env,
mode=function,
inherits=FALSE)))]
} else character(0)
}
pkgs - dir(.Library)
z - lapply(pkgs, findfuns)
names(z) - pkgs
Any recommendations on how to trap problems with require when using
findfuns? One bad package and the lapply above doesn't return anything.
For example:
findfuns(bcp)
Loading required package: bcp
Loading required package: DNAcopy
Error: package 'DNAcopy' could not be loaded
In addition: Warning message:
there is no package called 'DNAcopy' in: library(pkg, character.only = TRUE,
logical = TRUE, lib.loc = lib.loc)
require(bcp, character.only=TRUE)
Loading required package: bcp
Loading required package: DNAcopy
Error: package 'DNAcopy' could not be loaded
In addition: Warning message:
there is no package called 'DNAcopy' in: library(pkg, character.only = TRUE,
logical = TRUE, lib.loc = lib.loc)
I used try around the require call with options(error=recover) with
recover defined to be a do nothing function to avoid the stop, but then
there were other problems (e.g., unable to load shared library ...
LoadLibrary Failure: The specified module could not be found and Maximal
number of DLLs reached)
Besides bcp I saw problems with other packages, e.g., cairoDevice,
caMassClass, ... several others.
I'm using R 2.4.1with all CRAN packages installed that existed last week and
at least several Bioconductor packages installed by the biocLite procedure.
FWIW:
length(pkgs)
[1] 957
Thanks for any suggestions.
efg
Earl F. Glynn
Scientific Programmer
Stower Institute
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] Simple spectral analysis
Georg Hoermann [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] The data set: air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) airtemp = ts(T_air, start=c(1989,1), freq = 365) plot(airtemp) Maybe this will get you started using fft or spectrum -- I'm not sure why the spectrum answer is only close: air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) TempAirC - air$T_air Time - as.Date(air$Date, %d.%m.%Y) N - length(Time) oldpar - par(mfrow=c(4,1)) plot(TempAirC ~ Time) # Using fft transform - fft(TempAirC) # Extract DC component from transform dc - Mod(transform[1])/N periodogram - round( Mod(transform)^2/N, 3) # Drop first element, which is the mean periodogram - periodogram[-1] # keep first half up to Nyquist limit periodogram - periodogram[1:(N/2)] # Approximate number of data points in single cycle: print( N / which(max(periodogram) == periodogram) ) # plot spectrum against Fourier Frequency index plot(periodogram, col=red, type=o, xlab=Fourier Frequency Index, xlim=c(0,25), ylab=Periodogram, main=Periodogram derived from 'fft') # Using spectrum s - spectrum(TempAirC, taper=0, detrend=FALSE, col=red, main=Spectral Density) plot(log(s$spec) ~ s$freq, col=red, type=o, xlab=Fourier Frequency, xlim=c(0.0, 0.005), ylab=Log(Periodogram), main=Periodogram from 'spectrum') cat(Max frequency\n) maxfreq - s$freq[ which(max(s$spec) == s$spec) ] # Period will be 1/frequency: cat(Corresponding period\n) print(1/maxfreq) par(oldpar) efg Earl F. Glynn Scientific Programmer Stowers Institute __ R-help@stat.math.ethz.ch 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] Does strptime(...,tz=GMT) do anything?
Hi All In trying to correlate some tide gauge data I need to deal with varying timezones. From the documentation on strptime, it seemed that the tz variable might have some effect on the conversion, but I'm not seeing an effect. strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=PST)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=GMT)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=UTC)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=EST)+0 [1] 2006-12-01 01:02:00 EST What is the recommended way of handling this? Computing and adding offsets manually? strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=UTC)+3600*3 [1] 2006-12-01 04:02:00 EST Or am I doing something wrong with the strptime(..., tz=EST) function? Thanks for your time, Dave -- Dr. David Forrest [EMAIL PROTECTED](804)684-7900w [EMAIL PROTECTED] (804)642-0662h http://maplepark.com/~drf5n/ __ R-help@stat.math.ethz.ch 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] Simple spectral analysis
Earl F. Glynn wrote: Georg Hoermann [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] The data set: air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) airtemp = ts(T_air, start=c(1989,1), freq = 365) plot(airtemp) Maybe this will get you started using fft or spectrum -- I'm not sure why the spectrum answer is only close: The defaults for detrending and tapering could be involved. Putting, e.g., detrend=F gives me a spectrum with substantially higher low-frequency components. But what was the problem in the first place? spec.pgram(airtemp,xlim=c(0,10)) abline(v=1:10,col=red) shows a strong peak at 1 and maybe a weak peak at 2, and the other integer frequencies less pronounced. This seems reasonably in tune with x - (1:3652)/365 summary(lm(air$T_air ~ sin(2*pi*x)+cos(2*pi*x)+ sin(4*pi*x)+cos(4*pi*x) + sin(6*pi*x)+cos(6*pi*x)+x)) Call: lm(formula = air$T_air ~ sin(2 * pi * x) + cos(2 * pi * x) + sin(4 * pi * x) + cos(4 * pi * x) + sin(6 * pi * x) + cos(6 * pi * x) + x) Residuals: Min 1Q Median 3Q Max -16.3109 -2.3317 -0.1080 2.2063 10.6249 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept) 9.679040.11267 85.909 2e-16 *** sin(2 * pi * x) -2.645540.07967 -33.208 2e-16 *** cos(2 * pi * x) -7.735200.07938 -97.443 2e-16 *** sin(4 * pi * x) 0.929670.07948 11.696 2e-16 *** cos(4 * pi * x) 0.139820.07938 1.761 0.0783 . sin(6 * pi * x) 0.133200.07945 1.676 0.0937 . cos(6 * pi * x) 0.144800.07938 1.824 0.0682 . x -0.237730.01952 -12.179 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 3.393 on 3644 degrees of freedom Multiple R-Squared: 0.7486, Adjusted R-squared: 0.7482 F-statistic: 1550 on 7 and 3644 DF, p-value: 2.2e-16 air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) TempAirC - air$T_air Time - as.Date(air$Date, %d.%m.%Y) N - length(Time) oldpar - par(mfrow=c(4,1)) plot(TempAirC ~ Time) # Using fft transform - fft(TempAirC) # Extract DC component from transform dc - Mod(transform[1])/N periodogram - round( Mod(transform)^2/N, 3) # Drop first element, which is the mean periodogram - periodogram[-1] # keep first half up to Nyquist limit periodogram - periodogram[1:(N/2)] # Approximate number of data points in single cycle: print( N / which(max(periodogram) == periodogram) ) # plot spectrum against Fourier Frequency index plot(periodogram, col=red, type=o, xlab=Fourier Frequency Index, xlim=c(0,25), ylab=Periodogram, main=Periodogram derived from 'fft') # Using spectrum s - spectrum(TempAirC, taper=0, detrend=FALSE, col=red, main=Spectral Density) plot(log(s$spec) ~ s$freq, col=red, type=o, xlab=Fourier Frequency, xlim=c(0.0, 0.005), ylab=Log(Periodogram), main=Periodogram from 'spectrum') cat(Max frequency\n) maxfreq - s$freq[ which(max(s$spec) == s$spec) ] # Period will be 1/frequency: cat(Corresponding period\n) print(1/maxfreq) par(oldpar) efg Earl F. Glynn Scientific Programmer Stowers Institute __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Does strptime(...,tz=GMT) do anything?
Is EST a timezone on your system? You have not told us your system, but on most the timezone in the Eastern US is EST5EDT, not EST. Similarly with PST. (See ?as.POSIXct.) Remember that strptime returns an object of class POSIXlt and that has a 'isdst' field. The timezone controls that, but none of your examples are in a timezone that is on DST, nor would they be in EST5EDT or PST8PDT. Rather than add 0, I think you want to convert to POSIXct, specifying the timezone (a valid one). as.POSIXct(strptime(20061201 1:02,format=%Y%m%d %H:%M, tz=PST8PDT), tz=PST8PDT) [1] 2006-12-01 01:02:00 PST On Mon, 8 Jan 2007, David Forrest wrote: Hi All In trying to correlate some tide gauge data I need to deal with varying timezones. From the documentation on strptime, it seemed that the tz variable might have some effect on the conversion, but I'm not seeing an effect. strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=PST)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=GMT)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=UTC)+0 [1] 2006-12-01 01:02:00 EST strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=EST)+0 [1] 2006-12-01 01:02:00 EST What is the recommended way of handling this? Computing and adding offsets manually? strptime(20061201 1:02 PST,format=%Y%m%d %H:%M,tz=UTC)+3600*3 [1] 2006-12-01 04:02:00 EST Or am I doing something wrong with the strptime(..., tz=EST) function? Thanks for your time, Dave -- 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 __ R-help@stat.math.ethz.ch 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] scripts with littler
He missed o There is a new front-end Rscript which can be used for #! scripts and similar tasks. See help(Rscript) and 'An Introduction to R' for further details. and that is needed for #! scripts. (You cannot write #!/path/to/R -f as R is a shell script and so disallowed on most OSes.) As I understand the earlier question, if you have #! /usr/env cmd arg1 arg2 /usr/env is passed 'cmd arg1 arg2' as the name of the utility, at least under bash which says If the program is a file beginning with #!, the remainder of the first line specifies an interpreter for the program. The shell executes the specified interpreter on operating systems that do not handle this exe- cutable format themselves. The arguments to the interpreter consist of a single optional argument following the interpreter name ... Note the 'single'. This is detailed as part of the description of Rscript referred to in the NEWS item. I don't know how universal this is, but the Solaris Bourne shell does the same thing. François Pinard's idea of here documents is nice until you want to read from the script's stdin rather than the script itself. On Mon, 8 Jan 2007, Gabor Grothendieck wrote: Looks like it will be possible to write scripts with R 2.5.0 using the new -f flag and file(stdin). From https://svn.r-project.org/R/trunk/NEWS : oCommand-line R (and Rterm.exe under Windows) accepts the options '-f filename', '--file=filename' and '-e expression' to follow other script interpreters. These imply --no-save unless --save is specified. [..] ofile(stdin) is now recognized, and refers to the process's 'stdin' file stream whereas stdin() refers to the console. These may differ, for example for a GUI console, an embedded application of R or if --file= has been used. On 1/8/07, John Lawrence Aspden [EMAIL PROTECTED] wrote: Thanks, that's a really neat mechanism, ( I especially like the note to vim, which will save all my scripts having to end .R ) Is there any way to get at the command line and stdio though? With littler I can do things like: #!/usr/bin/env r print(argv) t=read.table(file=stdin()) so that I can write unix-style filters. Cheers, John. François Pinard wrote: I usually do something like: #!/bin/sh R --slave --vanilla EOF R script goes here... EOF # vim: ft=r If you need to search special places for packages, you may tweak exported environment variables between the first and second line. -- 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__ R-help@stat.math.ethz.ch 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] finer control of scales in xyplot
On 1/8/07, Benjamin Tyner [EMAIL PROTECTED] wrote: When plotting over multiple pages in lattice, I'd like to be able to have same scales within a page, but free scales between pages. In other words, something like: z-data.frame(x=1:100, y=runif(100), d=rep(1:2,50), p=rep(1:2,each=50)) plot-xyplot(y~x|d*p, data=z, scales=list(x=list(relation=free)), layout=c(1,2)) but within a page, to have common x-axes. As long as 'x' is sorted, I can get the desired effect by transforming x to a relative scale: plot-xyplot(y~unlist(with(z,tapply(x,p,function(x) (x-min(x))/diff(range(x)|d*p, data=z, layout=c(1,2)) except that I'd like the tickmark labels to be in the original units of 'x'. I've started looking at xscale.components.default to see whether it can work on a per-page (instead of per-panel) basis, but I get the nagging suspicion that I'm making this harder than it needs to be. Any assistance greatly appreciated. A nice solution is unlikely. As a general rule, the trellis object doesn't know anything about what layout it's going to be plotted with, and unfortunately the panel-specific scales are determined when the object is created, not when it is plotted (I don't remember all the reasons for this choice, but changing it would require a major overhaul). A similar task, row-specific or column-specific free scales, is difficult for the same reason. If I need to do this, I usually have in scales 1. relation=free 2. limits = list(lim1, lim2, ...) where lim1, lim2, etc are packet-specific limits (they have to be supplied explicitly). You can omit this if you can make sure your prepanel function gives you the right things. This will almost do what you want, but will repeat the ticks/labels for every panel. To suppress that you can additionally have 3. at = list(TRUE, NULL, ...) etc where NULL means ticks/labels won't be drawn. This doesn't really help, because the space will still be wasted, so finally, 4. add par.settings = list(layout.heights = list(axis.panel = c(1, 0, ...))) -Deepayan __ R-help@stat.math.ethz.ch 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] A question about R environment
Hi all, I created environment mytoolbox by : mytoolbox - new.env(parent=baseenv()) Is there anyway I put it in the search path ? If you need some background : In a project, I often write some small functions, and load them into my workspace directly, so when I list the objects with ls(), it looks pretty messy. So I am wondering if it is possible to creat an environment, and put these tools into this environment. For example, I have functionsfun1(), fun2() .. and creat an environment mytoolbox which contains all these functions. And it should be somewhere in the search path: .GlobalEnvmytoolboxpackage:methods __ R-help@stat.math.ethz.ch 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] A question about R environment
Try this: e - new.env() e$f - function(x)x attach(e) search() [1] .GlobalEnve package:stats [4] package:graphics package:grDevices package:utils [7] package:datasets package:methods Autoloads [10] package:base f function(x)x On 1/8/07, Tong Wang [EMAIL PROTECTED] wrote: Hi all, I created environment mytoolbox by : mytoolbox - new.env(parent=baseenv()) Is there anyway I put it in the search path ? If you need some background : In a project, I often write some small functions, and load them into my workspace directly, so when I list the objects with ls(), it looks pretty messy. So I am wondering if it is possible to creat an environment, and put these tools into this environment. For example, I have functionsfun1(), fun2() .. and creat an environment mytoolbox which contains all these functions. And it should be somewhere in the search path: .GlobalEnvmytoolbox package:methods __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Partial proportional odds logistic regression
Just a follow-up note on my last posting. I still have not had any
replies from the R-experts our there that use partial proportional odds
regression (and I have to hope that there are some of you!) but I do
think that I have figured out how to perform the unconstrained partial
proportional odds model using vglm. I show this code below for the
benefit of others that may want to try it (or point out my errors) using
one of the datasets in Petersen and Harrell's paper (Appl Stat 1990).
However, I remain open for suggestions on how to implement the
unconstrained partial proportional odds model.
--
library(VGAM)
library(MASS)
library(Design)
###
# Nausea dataset
# Peterson and Harrell. Applied Statistics 1990, 39(2): 205-217
nausea.short - data.frame(matrix(nrow=12, ncol=3)) #Table 2
colnames(nausea.short) - c('nausea', 'cisplatin', 'freq')
nausea.short[,1] - ordered(rep(seq(0,5,1),2),
labels=seq(0,5,1))
nausea.short[,2] - c(rep(0,6), rep(1,6))
nausea.short[,3] - c(43,39,13,22,15,29,7,7,3,12,15,14)
# Proportional odds ordinal logistic regression: 3 options
polr(nausea ~ cisplatin, weights=freq, data=nausea.short,
method='logistic')
lrm(nausea ~ cisplatin, weights=freq, data=nausea.short)
vglm(nausea ~ cisplatin, weights=freq, data=nausea.short,
family=cumulative(parallel=T, reverse=T))
# Unconstrained partial proportional odds ordinal logistic regression
vglm(nausea ~ cisplatin, weights=freq, data=nausea.short,
family=cumulative(parallel=F, reverse=T))
--
The results obtained with this approach appear consistent with those
presented in Table 3 of the paper. However, the code for the
unconstrained partial proportional odds model is so simple (just one
letter is different than in the proportional odds model!) that I wonder
if there is not room for error here that I am too inexperienced to
identify.
Again, help with the constrained model would be greatly appreciated.
Brant Inman
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Re: [R] A question about R environment
[Tong Wang]
I created environment mytoolbox by : mytoolbox -
new.env(parent=baseenv()). Is there anyway I put it in the search
path? In a project, I often write some small functions, and load them
into my workspace directly, so when I list the objects with ls(), it
looks pretty messy. So I am wondering if it is possible to creat an
environment, and put these tools into this environment. For example,
I have functions fun1(), fun2() ... and creat an environment mytoolbox
which contains all these functions. And it should be somewhere in the
search path: .GlobalEnv mytoolbox package:methods.
Here is a trick, shown as a fairly simplified copy of my ~/.Rprofile.
It allows for a few simple functions always available, yet without
having to create a package, and leaving ls() and any later .RData file
unencumbered.
The idea is to use local() to prevent any unwanted clutter to leak out
(my real ~/.Rprofile holds more than shown below and use temporary
variables), to initialise a list meant to hold a bunch of functions or
other R things, and to save that list on the search path.
This example also demonstrate a few useful functions for when I read the
R mailing list. I often need to transfer part of emails containing
code excerpts within the window where R executes, while removing
quotation marks, white lines and other noise. I merely highlight-select
part of the message with the mouse, and then, within R, do things like:
xs() source the highlighted region
xd() read in a data.frame
xm() read in a matrix
xe() evaluate and print an expression
xv() read a list of values as a vector
The list above in decreasing order of usefulness (for me). Except for
xs(), which has no automatic printout, you may either let the others
print what they got, or assign their value to some variable. Arguments
are also possible, for example like this:
xd(T) read in a data.frame when the first line holds column names
if (interactive()) {
local({
fp.etc - list()
fp.etc$xsel.vector - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
scan(connexion, ...)
}
fp.etc$xsel.dataframe - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
read.table(connexion, ...)
}
fp.etc$xsel.matrix - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
data.matrix(read.table(connexion, ...))
}
fp.etc$xsel.eval - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
eval(parse(connexion, ...))
}
fp.etc$xsel.source - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
source(connexion, ...)
}
fp.etc$xselection - function ()
{
lignes - suppressWarnings(readLines('clipboard'))
lignes - lignes[lignes != '']
stopifnot(length(lignes) != 0)
marge - substr(lignes, 1, 1)
while (all(marge %in% c('', '+', ':', '|'))
|| all(marge == ' ')) {
lignes - substring(lignes, 2)
marge - substr(lignes, 1, 1)
}
lignes
}
fp.etc$xv - fp.etc$xsel.vector
fp.etc$xd - fp.etc$xsel.dataframe
fp.etc$xm - fp.etc$xsel.matrix
fp.etc$xe - fp.etc$xsel.eval
fp.etc$xs - fp.etc$xsel.source
attach(fp.etc, warn=FALSE)
})
}
# vim: ft=r
--
François Pinard http://pinard.progiciels-bpi.ca
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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] A question about R environment
Please, don't reinvent the wheel: putting functions in a dedicated
environment is one of the things done by R packages (together with a
good documentation of the function, and making them easily installable
on any R implementation). So, this is probably the time for you to read
the Writing R extensions manual, and to start implementing your own R
package!
Best,
Philippe Grosjean
François Pinard wrote:
[Tong Wang]
I created environment mytoolbox by : mytoolbox -
new.env(parent=baseenv()). Is there anyway I put it in the search
path? In a project, I often write some small functions, and load them
into my workspace directly, so when I list the objects with ls(), it
looks pretty messy. So I am wondering if it is possible to creat an
environment, and put these tools into this environment. For example,
I have functions fun1(), fun2() ... and creat an environment mytoolbox
which contains all these functions. And it should be somewhere in the
search path: .GlobalEnv mytoolbox package:methods.
Here is a trick, shown as a fairly simplified copy of my ~/.Rprofile.
It allows for a few simple functions always available, yet without
having to create a package, and leaving ls() and any later .RData file
unencumbered.
The idea is to use local() to prevent any unwanted clutter to leak out
(my real ~/.Rprofile holds more than shown below and use temporary
variables), to initialise a list meant to hold a bunch of functions or
other R things, and to save that list on the search path.
This example also demonstrate a few useful functions for when I read the
R mailing list. I often need to transfer part of emails containing
code excerpts within the window where R executes, while removing
quotation marks, white lines and other noise. I merely highlight-select
part of the message with the mouse, and then, within R, do things like:
xs() source the highlighted region
xd() read in a data.frame
xm() read in a matrix
xe() evaluate and print an expression
xv() read a list of values as a vector
The list above in decreasing order of usefulness (for me). Except for
xs(), which has no automatic printout, you may either let the others
print what they got, or assign their value to some variable. Arguments
are also possible, for example like this:
xd(T) read in a data.frame when the first line holds column names
if (interactive()) {
local({
fp.etc - list()
fp.etc$xsel.vector - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
scan(connexion, ...)
}
fp.etc$xsel.dataframe - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
read.table(connexion, ...)
}
fp.etc$xsel.matrix - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
data.matrix(read.table(connexion, ...))
}
fp.etc$xsel.eval - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
eval(parse(connexion, ...))
}
fp.etc$xsel.source - function (...) {
connexion - textConnection(xselection())
on.exit(close(connexion))
source(connexion, ...)
}
fp.etc$xselection - function ()
{
lignes - suppressWarnings(readLines('clipboard'))
lignes - lignes[lignes != '']
stopifnot(length(lignes) != 0)
marge - substr(lignes, 1, 1)
while (all(marge %in% c('', '+', ':', '|'))
|| all(marge == ' ')) {
lignes - substring(lignes, 2)
marge - substr(lignes, 1, 1)
}
lignes
}
fp.etc$xv - fp.etc$xsel.vector
fp.etc$xd - fp.etc$xsel.dataframe
fp.etc$xm - fp.etc$xsel.matrix
fp.etc$xe - fp.etc$xsel.eval
fp.etc$xs - fp.etc$xsel.source
attach(fp.etc, warn=FALSE)
})
}
# vim: ft=r
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Re: [R] A question about R environment
sourceTo() in R.utils will allow you to source() a file into an environment. /Henrik On 1/9/07, Gabor Grothendieck [EMAIL PROTECTED] wrote: Try this: e - new.env() e$f - function(x)x attach(e) search() [1] .GlobalEnve package:stats [4] package:graphics package:grDevices package:utils [7] package:datasets package:methods Autoloads [10] package:base f function(x)x On 1/8/07, Tong Wang [EMAIL PROTECTED] wrote: Hi all, I created environment mytoolbox by : mytoolbox - new.env(parent=baseenv()) Is there anyway I put it in the search path ? If you need some background : In a project, I often write some small functions, and load them into my workspace directly, so when I list the objects with ls(), it looks pretty messy. So I am wondering if it is possible to creat an environment, and put these tools into this environment. For example, I have functionsfun1(), fun2() .. and creat an environment mytoolbox which contains all these functions. And it should be somewhere in the search path: .GlobalEnvmytoolbox package:methods __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Simple spectral analysis
Peter Dalgaard wrote: Earl F. Glynn wrote: The defaults for detrending and tapering could be involved. Putting, e.g., detrend=F gives me a spectrum with substantially higher low-frequency components. But what was the problem in the first place? understanding how this things work in R compared to other packages 8-) Thanks a lot for the help. I will post the script when its ready (an introduction for our biology students to time series, just 8 hours) Georg -- Georg Hoermann, Dep. of Hydrology, Ecology, Kiel University, Germany +49/431/23761412, mo: +49/171/4995884, icq:348340729, skype: ghoermann __ R-help@stat.math.ethz.ch 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] no linear model with many objects
Hi all, Is any way to estimate the parameters of a curve, not manualy, from many subsets of my dataset [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] ACCESS/Office : connecting
It is easy with package RODBC. Connecting to databases is discussed in the 'R Data Import/Export' manual. On Mon, 8 Jan 2007, Milton Cezar Ribeiro wrote: How can I connect to a ACCESS (.mdb) file? In fact, I would like to connect to a blank file, write a data.frame as table and after that INSERT records using some insert command. Kind regards, Miltinho Brazil -- 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 __ R-help@stat.math.ethz.ch 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] Simple spectral analysis
Hi without beeing specific in spectrum analysis you will get frequencies and spectral densities fro spectrum() From help page An object of class spec, which is a list containing at least the following components: freq vector of frequencies at which the spectral density is estimated. (Possibly approximate Fourier frequencies.) The units are the reciprocal of cycles per unit time (and not per observation spacing): see Details below. spec Vector (for univariate series) or matrix (for multivariate series) of estimates of the spectral density at frequencies corresponding to freq. snip This is the important part: **The result is returned invisibly if plot is true.** So if you call spectrum(data) you will get plot but in case sp - spectrum(data) you will get also object sp which has above mentioned components. Actual periods are obtainable by n/sp$freq HTH Petr On 8 Jan 2007 at 17:12, Georg Hoermann wrote: Date sent: Mon, 08 Jan 2007 17:12:34 +0100 From: Georg Hoermann [EMAIL PROTECTED] To: r-help@stat.math.ethz.ch Subject:[R] Simple spectral analysis Hello world, I am actually trying to transfer a lecture from Statistica to R and I ran into problems with spectral analysis, I think I just don't get it 8-( (The posting from FFT, frequs, magnitudes, phases from 2005 did not enlighten me) As a starter for the students I have a 10year data set of air temperature with daily values and I try to get a periodogram where the annual period (365 days) should be clearly visible (in statistica I can get the frequencies and the period). I tried the spectrum() and pgram() functions, but did not find a way through... The final aim would be to get the periodogram (and the residuals from the reassembled data set...) Thanks and greetings, Georg The data set: air = read.csv(http://www.hydrology.uni-kiel.de/~schorsch/air_temp.csv;) airtemp = ts(T_air, start=c(1989,1), freq = 365) plot(airtemp) -- Georg Hoermann, Dep. of Hydrology, Ecology, Kiel University, Germany +49/431/23761412, mo: +49/171/4995884, icq:348340729, skype: ghoermann __ R-help@stat.math.ethz.ch 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. Petr Pikal [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch 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] no linear model with many objects
Hi On 9 Jan 2007 at 9:17, Zaphiris Abas wrote: From: Zaphiris Abas [EMAIL PROTECTED] To: r-help@stat.math.ethz.ch Date sent: Tue, 9 Jan 2007 09:17:50 +0200 Subject:[R] no linear model with many objects Hi all, Is any way to estimate the parameters of a curve, not manualy, from many subsets of my dataset Most probably yes. But you probably meant *how*. To continue questioning see. PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Maybe you are looking for nlme. HTH Petr Petr Pikal [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch 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.
