[R] Reshape (pivot) question
Hi R-users,
I have a data set like this (first ten rows):
id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 1
NA ID1564262 1562 6.4.2006 12:00 1 NA ID1564264 1365 14.2.2006 14:35
1 50 ID1564265 1342 7.4.2006 14:30 2 50 ID1564266 1648 7.4.200614:30
2 50 ID1564267 1263 10.2.2006 15:45 2 10 ID1564267 1263
10.2.200615:45
3 10 ID1564269 5646 13.5.2006 17:02 3 10 ID1564270 7561
13.5.200617:02
1 10 ID1564271 1676 15.5.2006 20:41 2 20
How can I do a new (pivot?) data.frame in R which I can achieve by MS SQL:
select eala,
datepart(month, date) as month,
datepart(year, date) as year,
count(distinct id) as id_count,
count(distinct patient_id) as patient_count,
count(distinct(case when class = 1 then code else null end)) as count_1,
count(distinct(case when class = 2 then code else null end)) as count_2,
count(distinct(case when class = 3 then code else null end)) as count_3,
into temp2
from temp1
group by datepart(month, date), datepart(year, date), eala
order by datepart(month, date), datepart(year, date), eala
I tried something like this but could not go further:
stats - function(x) {
count - function(x) length(na.omit(x))
c(
n = count(x),
uniikit = length(unique(x))
)
}
library(reshape)
attach(dframe)
dfm - melt(dframe, measure.var=c(id,patient_id), id.var=c(code,this
should be month,this should be year), variable_name=variable)
cast(dfm, code + month + year ~ variable, stats)
Regards,
Lauri
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[R] interaction term and scatterplot3d
Dear Listers, I would be interested in representing a trend surface including an interaction term z = f(x,y,x.y) - eg the type of chart obtained with persp() or wireframe(), then adding datapoints as a cloud, ideally with dots which are under the surface in a color, and those who are above in another color. An other option would be to draw segments between the dots and the ground of the chart. scatterplot3d looks like being close to do such things except it does not to include (to my knowledge) a coefficient for the interaction term (thus just model z = f(x,y). Does anybody has an idea where to start with this and the main steps? Or a place/website where some script examples can be found? Patrick __ 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] Another subsetting enigma
jim holtman wrote:
matches - sapply(result, function(x){
+ .comma - strsplit(x, ',')[[1]] # get the fields
+ any(my.list %in% .comma)
+ })
Thanks for that!
Joh
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[R] Difficulties with dataframe filter using elements from an array created using a for loop or seq()
Hi All-
This seems like such a pathetic problem to be posting about, but I have no
idea why this testcase does not work. I have tried this using R 2.4.1,
2.4.0, 2.3.0, and 2.0.0 on several different computers (Mac OS 10.4.8,
Windows XP, Linux). Below the signature, you will find my test case R code.
My point in this folly is to take a dataframe of 300,000 rows, create a
filter based on two of the rows, and count the number of rows in the
filtered and unfiltered dataframe. One column in the filter only has the
numbers 0.05, 0.15, 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95, so I
thought that I could just iterate in a for loop and get the job done. Just
the simple single column filter case is presented here. Obviously, there are
only ten numbers, so the manual method is easy, but I would like to have a
more flexible program. (Plus it worries me if the simple things don't do
what I expect... :-) )
From the output, you can see that the loop using the handmadevector that
creates a filter and counts the elements, correctly finds one match for each
element in the vector, but the seq() and for loop produced vectors each give
a mixture of true and false matches.
Can anyone tell me why the loopvector and seqvector do not provide the
same output as the handmadevector.
Thank you for your assistance!
Todd
--
Todd A. Johnson
Research Associate, Laboratory for Medical Informatics
SNP Research Center,RIKEN
1-7-22Suehiro,Tsurumi-ku,Yokohama
Kanagawa 230-0045,Japan
Cellphone: 090-5309-5867
E-mail: [EMAIL PROTECTED]
Here's the testcase, with the sample code between the lines and the output
following:
_
## Set up three different vectors, each with the numbers 0.05, 0.15, 0.25,
0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95
## each of which is used to select records from a dataframe based on
equality to a particular column
## The first vector is created by using a for loop
loopvector - c()
for (i in 0:9){
loopvector - c(loopvector, (i*0.10)+0.05);
}
## The second vector is made by hand
handmadevector - c(0.05, 0.15, 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85,
0.95)
## The third vector is made using seq()
seqvector - seq(0.05, 0.95, 0.10)
## Are the vectors the same?
all.equal(loopvector, handmadevector)
all.equal(loopvector, seqvector)
print(handmadevector)
print(loopvector)
print(seqvector)
## As a simple testcase, I create a dataframe with two variables, a varA of
dummy data, and bBins
## which is the column on which I was trying to filter.
a - c(0,1,2,0,1,3,4,5,3,5)
b - c(0.05,0.15,0.25,0.35,0.45,0.55,0.65,0.75,0.85,0.95)
testdf - data.frame(varA = a, bBins = b)
attach(testdf)
## Loop through each of the vectors, create a filter on the dataframe based
on equality with the current iteration,
## and print that number and the count of records in the dataframe that
match that number.
for (i in loopvector){
aqs_filt - bBins==i;
print(i);
print(length(testdf$varA[aqs_filt]));
}
for (i in handmadevector){
aqs_filt - bBins==i;
print(i);
print(length(testdf$varA[aqs_filt]));
}
for (i in seqvector){
aqs_filt - bBins==i;
print(i);
print(length(testdf$varA[aqs_filt]));
}
_
Here's the output from R 2.4.1 running on an Apple 12 Powerbook.
## Set up three different vectors, each with the numbers 0.05, 0.15, 0.25,
0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95
## each of which is used to select records from a dataframe based on equality
to a particular column
## The first vector is created by using a for loop
loopvector - c()
for (i in 0:9){
+ loopvector - c(loopvector, (i*0.10)+0.05);
+ }
## The second vector is made by hand
handmadevector - c(0.05, 0.15, 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85,
0.95)
## The thirs vector is made using seq()
seqvector - seq(0.05, 0.95, 0.10)
## Are the vectors the same?
all.equal(loopvector, handmadevector)
[1] TRUE
all.equal(loopvector, seqvector)
[1] TRUE
print(handmadevector)
[1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
print(loopvector)
[1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
print(seqvector)
[1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## As a simple testcase, I create a dataframe with two variables, a varA of
dummy data, and bBins
## which is the column on which I was trying to filter.
a - c(0,1,2,0,1,3,4,5,3,5)
b - c(0.05,0.15,0.25,0.35,0.45,0.55,0.65,0.75,0.85,0.95)
testdf - data.frame(varA = a, bBins = b)
attach(testdf)
## Loop through each of the vectors, create a filter on the dataframe based on
equality with the current iteration,
## and print that number and the count of records in the dataframe that match
that number.
for (i in loopvector){
+ aqs_filt - bBins==i;
+ print(i);
+ print(length(testdf$varA[aqs_filt]));
+ }
[1] 0.05
[1] 1
[1] 0.15
[1] 0
[1] 0.25
[1] 1
[1] 0.35
[1] 0
[1] 0.45
[1] 1
[1] 0.55
[1] 1
[1] 0.65
[1] 0
[1] 0.75
[1] 0
[1] 0.85
[1] 0
[1] 0.95
[1] 0
for (i in
Re: [R] bootstrapping Levene's test
[EMAIL PROTECTED] wrote:
Hello all,
I am low down on the learning curve of R but so far I have had little
trouble using most of the packages. However, recently I have run into
a wall when it comes to bootstrapping a Levene's test (from the car
package) and thought you might be able to help. I have not been able
to find R examples for the boot package where the test statistic
specifically uses a grouping variable (or at least a simple example
with this condition). I would like to do a non-parametric bootstrap
to eventually get 95% confidence intervals using the boot.ci command.
I have included the coding I have tried on a simple data set below. If
anyone could provide some help, specifically with regards to how the
statistic arguement should be set up in the boot package, it would
be greatly appreciated.
library(boot)
library(car)
data-c(2,45,555,1,77,1,2,1,2,1)
group-c(1,1,1,1,1,2,2,2,2,2)
levene.test(data,group)
Levene's Test for Homogeneity of Variance
Df F value Pr(F)
group 1 1.6929 0.2294
8
stat-function(a){levene.test(a,group)}
trial1-boot(data,statistic,100)
Error in statistic(data, original, ...) : unused argument(s) ( ...)
One problem is that levene.test() returns an ANOVA table, which is not
a statistic. Looking inside levene.test() to see what might be used as
a statistic, for the two-group case it seems like you could do something
like this:
library(boot)
library(car)
set.seed(671969)
df - data.frame(Y = c(rnorm(100,0,1), rnorm(100,0,1)),
G = rep(c(1,2), each = 100))
boot.levene - function(data,indices){
levene.diff - diff(tapply(df$Y[indices],
list(df$G[indices]), mad))
return(levene.diff)
}
first.try - boot(df, boot.levene, 1000)
first.try
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = df, statistic = boot.levene, R = 1000)
Bootstrap Statistics :
original biasstd. error
t1* -0.1944924 0.02439172 0.1753512
boot.ci(first.try, index=1, type=bca)
BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
Based on 1000 bootstrap replicates
CALL :
boot.ci(boot.out = first.try, type = bca, index = 1)
Intervals :
Level BCa
95% (-0.5772, 0.1159 )
Calculations and Intervals on Original Scale
Best regards,
Kevin
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Chuck Cleland, Ph.D.
NDRI, Inc.
71 West 23rd Street, 8th floor
New York, NY 10010
tel: (212) 845-4495 (Tu, Th)
tel: (732) 512-0171 (M, W, F)
fax: (917) 438-0894
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Re: [R] Difficulties with dataframe filter using elements from an array created using a for loop or seq()
FAQ Q7.31 On Tue, 20 Feb 2007, Todd A. Johnson wrote: Hi All- This seems like such a pathetic problem to be posting about, but I have no idea why this testcase does not work. I have tried this using R 2.4.1, 2.4.0, 2.3.0, and 2.0.0 on several different computers (Mac OS 10.4.8, Windows XP, Linux). Below the signature, you will find my test case R code. My point in this folly is to take a dataframe of 300,000 rows, create a filter based on two of the rows, and count the number of rows in the filtered and unfiltered dataframe. One column in the filter only has the numbers 0.05, 0.15, 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95, so I thought that I could just iterate in a for loop and get the job done. Just the simple single column filter case is presented here. Obviously, there are only ten numbers, so the manual method is easy, but I would like to have a more flexible program. (Plus it worries me if the simple things don't do what I expect... :-) ) From the output, you can see that the loop using the handmadevector that creates a filter and counts the elements, correctly finds one match for each element in the vector, but the seq() and for loop produced vectors each give a mixture of true and false matches. Can anyone tell me why the loopvector and seqvector do not provide the same output as the handmadevector. Thank you for your assistance! Todd -- 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] tree()
This is a function of your data and the tuning parameters you chose to use. See ?tree.control. On Tue, 20 Feb 2007, stephenc wrote: Hi I am trying to use tree() to classify movements in a futures contract. My data is like this: diff dip dim adx 1 0100.08650.100.0 2 0 93.185402044.5455 93.18540 3 0 90.309951549.1169 90.30995 4 1 85.22030 927.0419 85.22030 5 1 85.36084 785.6480 85.36084 6 0 85.72627 663.3814 85.72627 7 0 78.06721 500.1113 78.06721 8 1 69.59398 376.7558 69.59398 9 1 71.15429 307.4533 71.15429 10 1 71.81023 280.6238 71.81023 plus another 6000 lines The cpus example works fine and I am trying this: tree.model - tree(as.factor(indi$diff) ~ indi$dim + indi$dip + indi$adx, indi[1:4000,]) Oh, please! use the data= argument properly. -- 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.
[R] Mahalanobis distance and probability of group membership using Hotelling's T2 distribution
I want to calculate the probability that a group will include a particular
point using the squared Mahalanobis distance to the centroid. I understand
that the squared Mahalanobis distance is distributed as chi-squared but that
for a small number of random samples from a multivariate normal population
the Hotellings T2 (T squared) distribution should be used.
I cannot find a function for Hotelling's T2 distribution in R (although from
a previous post I have been provided with functions for the Hotelling Test).
My understanding is that the Hotelling's T2 distribution is related to the F
distribution using the equation:
T2(u,v) = F(u, v-u+1)*vu/(v-u+1)
where u is the number of variables and v the number of group members.
I have written the R code below to compare the results from the chi-squared
distribution with the Hotelling's T2 distribution for probability of a
member being included within a group.
Please can anyone confirm whether or not this is the correct way to use
Hotelling's T2 distribution for probability of group membership. Also, when
testing a particular group member, is it preferable to leave that member out
when calculating the centre and covariance of the group for the Mahalanobis
distances?
Thanks
Mike White
## Hotelling T^2 distribution function
ph-function(q, u, v, ...){
# q vector of quantiles as in function pf
# u number of independent variables
# v number of observations
if (!v u+1) stop(n must be greater than p+1)
df1 - u
df2 - v-u+1
pf(q*df2/(v*u), df1, df2, ...)
}
# compare Chi-squared and Hotelling T^2 distributions for a group member
u-3
v-10
set.seed(1)
mat-matrix(rnorm(v*u), nrow=v, ncol=u)
MD2-mahalanobis(mat, center=colMeans(mat), cov=cov(mat))
d-MD2[order(MD2)]
# select a point midway between nearest and furthest from centroid
dm-d[length(d)/2]
1-ph(dm,u,v)# probability using Hotelling T^2 distribution
# [1] 0.6577069
1-pchisq(dm, u) # probability using Chi-squared distribution
# [1] 0.5538466
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Re: [R] Lengend function and moving average plot
--- amna khan [EMAIL PROTECTED] wrote: Sir I am very new user of R. I am not understanding the how to write the plot description in box outside the plot. Have a look at http://finzi.psych.upenn.edu/R/Rhelp02a/archive/68585.html You should read up on par ?par I hope this helps __ 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] Problems with obtaining t-tests of regression coefficients applying consistent standard errors after run 2SLS estimation. Clearer !!!!!
First I have to say I am sorry because I have not been so clear in my previous e-mails. I will try to explain clearer what it is my problem. I have the following model: lnP=Sc+Ag+Ag2+Var+R+D In this model the variable Sc is endogenous and the rest are all objective exogenous variables. I verified that Sc is endogenous through a standard Hausman test. To determine this I defined before a new instrumental variable, I2. Also I detected through a Breusch Pagan Test a problem of heteroskedasticity. With the intention to avoid the problem of the endogenous variable and the heteroskedasticity I want to apply first the technique 2SLS and then based in these results I want to obtain the t-tests of the coefficients applying Heteroskedasticity Consistent Standard Errors (HCSE) or Huber-White errors. Like I showed above I have just one structural equation in the model. In this situation, to apply 2SLS in R until I know there two possible ways: First to use the function tsls() from package sem, or second, to use the function systemfit() from package systemfit. I thought that systemfit was for situations when there are more than one structural equation in the model. Anyway I probed with the two ways and I obtained similar results. Below, I show the program lines: *Program lines 1:* * * * First option: applying tsls * *library (sem)* *Reg1 -tsls (LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D) * *summary (Reg1)* * * * Second option: applying systemfit * *library (systemfit)* *RS - LnP~Sc+Ag+Ag2+Var+R+D # structural equation* *Inst - ~I2+Ag+Ag2+Var+R+D# instrumental variables* *labels - list(RS)* *system - list(RS)* *Reg2 - systemfit(2SLS, system, labels, Inst, saveMemory=TRUE) * *summary (Reg2)* Now I want to obtain the t-tests of the coefficients but applying the HCSE. I know two different ways to obtain them: First, applying the function robcov() from package Design, or Second, applying coeftest() and vcovHV() from packages lmtest and sandwich. The program lines are the following: *Program lines 2:* * First option: using robcov() * *library (Design)* *options(scipen=20)* *robcov(Reg1) ### I tried with Reg 2 too* ** ** ** ***Second option: using coeftest and vcovHC * *library (lmtest)* *library (sandwich)* *coeftest (Reg1, vcov=vcovHC(Reg1 or Reg2, type=HC0)) ### I tried with Reg 2 too* In the two cases after trying to apply robcov or coeftest I obtained a message of error: *With robcov:* * Error in rep.default(1, p) : rep() incorrect type for second argument * * * *With coeftest:* *** **Error in terms.default(object) : no terms component* In the following lines I copy all the sequence together from R. If I try with systemfit instead of tsls I obtain the same result: *Program lines 3:* *ibrary (sem)* * Reg1 -tsls(LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D)* * library (Design)* *Loading required package: Hmisc* *Loading required package: chron* *Hmisc library by Frank E Harrell Jr* *Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview')* *to see overall documentation.* *NOTE:Hmisc no longer redefines [.factor to drop unused levels when* *subsetting. To get the old behavior of Hmisc type dropUnusedLevels().* *Loading required package: survival* *Loading required package: splines* *Attaching package: 'survival'* *The following object(s) are masked from package:Hmisc :* * untangle.specials * *Design library by Frank E Harrell Jr* *Type library(help='Design'), ?Overview, or ?Design.Overview')* *to see overall documentation.* *Attaching package: 'Design'* *The following object(s) are masked from package:survival :* * cox.zph Surv survfit * *The following object(s) are masked from package:Hmisc :* * .noGenenerics .R. .SV4. * * options(scipen=20)* * robcov(Reg1)* *Error in rep.default(1, p) : rep() incorrect type for second argument* * library (lmtest)* *Loading required package: zoo* *Attaching package: 'lmtest'* *The following object(s) are masked from package:Design :* * lrtest * * library (sandwich)* * coeftest (Reg1, vcov=vcovHC(Reg1, type=HC0))* *Error in terms.default(object) : no terms component* ** I would like to solve these problems and to understand what the meanings of the errors messages are. Also I want to know if there is another way to obtain the HCSE through a function, because if I can not fix the problem my last alternative is to do it manually. I will thank a lot if somebody can help me Best wishes Guillermo [[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] Reshape (pivot) question
Haven't quite learned to 'cast' yet, but I have always used the 'apply'
functions for this type of processing:
x - id patient_id date code class eala
+ ID1564262 1562 6.4.200612:00 1 NA
+ ID1564262 1562 6.4.200612:00 1 NA
+ ID1564264 1365 14.2.200614:35 1 50
+ ID1564265 1342 7.4.200614:30 2 50
+ ID1564266 1648 7.4.200614:30 2 50
+ ID1564267 1263 10.2.200615:45 2 10
+ ID1564267 1263 10.2.200615:45 3 10
+ ID1564269 5646 13.5.200617:02 3 10
+ ID1564270 7561 13.5.200617:02 1 10
+ ID1564271 1676 15.5.200620:41 2 20
x.in - read.table(textConnection(x), header=TRUE)
# 'by' seems to drop NAs so convert to a character string for processing
x.in$eala - ifelse(is.na(x.in$eala), NA, as.character(x.in$eala))
# convert date to POSIXlt so we can access the year and month
myDate - strptime(x.in$date, %d.%m.%Y%H:%M)
x.in$year - myDate$year + 1900
x.in$month - myDate$mon+1
# split the data by eala, year, month and summarize
x.by - by(x.in, list(x.in$eala, x.in$year, x.in$month), function(x){
+ data.frame(eala=x$eala[1], month=x$month[1], year=x$year[1],
+ icount=length(unique(x$id)), pcount=length(unique(x$patient_id)),
+ count1=sum(x$class == 1), count2=sum(x$class == 2),
count3=sum(x$class == 3))
+ })
# convert back to a data frame
do.call(rbind, x.by)
eala month year icount pcount count1 count2 count3
1 10 2 2006 1 1 0 1 1
2 50 2 2006 1 1 1 0 0
3 50 4 2006 2 2 0 2 0
4 NA 4 2006 1 1 2 0 0
5 10 5 2006 2 2 1 0 1
6 20 5 2006 1 1 0 1 0
On 2/20/07, Lauri Nikkinen [EMAIL PROTECTED] wrote:
Hi R-users,
I have a data set like this (first ten rows):
id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 1
NA ID1564262 1562 6.4.2006 12:00 1 NA ID1564264 1365 14.2.2006 14:35
1 50 ID1564265 1342 7.4.2006 14:30 2 50 ID1564266 1648
7.4.200614:30
2 50 ID1564267 1263 10.2.2006 15:45 2 10 ID1564267 1263
10.2.200615:45
3 10 ID1564269 5646 13.5.2006 17:02 3 10 ID1564270 7561
13.5.200617:02
1 10 ID1564271 1676 15.5.2006 20:41 2 20
How can I do a new (pivot?) data.frame in R which I can achieve by MS SQL:
select eala,
datepart(month, date) as month,
datepart(year, date) as year,
count(distinct id) as id_count,
count(distinct patient_id) as patient_count,
count(distinct(case when class = 1 then code else null end)) as count_1,
count(distinct(case when class = 2 then code else null end)) as count_2,
count(distinct(case when class = 3 then code else null end)) as count_3,
into temp2
from temp1
group by datepart(month, date), datepart(year, date), eala
order by datepart(month, date), datepart(year, date), eala
I tried something like this but could not go further:
stats - function(x) {
count - function(x) length(na.omit(x))
c(
n = count(x),
uniikit = length(unique(x))
)
}
library(reshape)
attach(dframe)
dfm - melt(dframe, measure.var=c(id,patient_id), id.var=c
(code,this
should be month,this should be year), variable_name=variable)
cast(dfm, code + month + year ~ variable, stats)
Regards,
Lauri
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What is the problem you are trying to solve?
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[R] Sample size
Dear R-list, I have to design the validation of a score (ordinal values between 0 and 6) reputed to separate 4 groups of patients with known frequencies in the population. I think the more accurate is to calculate sample size under median test. Is there a function for that in R (not in the pwr package)? Thanks in advance, with all my best, erik S. = Erik-André SAULEAU SEAIM Centre Hospitalier 87, Avenue d'Altkirch BP 1070 68051 Mulhouse Cédex Tel: 03 89 64 67 53 Mel: [EMAIL PROTECTED] Web: www.ch-mulhouse.fr = Registre des Cancers du Haut-Rhin 9, Rue du Dr Mangeney BP 1370 68070 Mulhouse Cédex Tel: 03 89 64 62 51 Web: www.arer68.org = ** Afin d'eviter toute propagation de virus informatique, et en complement des dispositifs en place, ce message (et ses pieces jointes s'il y en a) a ete automatiquement analyse par un antivirus de messagerie. ** [[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 management uestion [Broadcast]
I don't see why making copies of the columns you need inside the loop is
better memory management. If the data are in a matrix, accessing
elements is quite fast. If you're worrying about speed of that, do what
Charles suggest: work with the transpose so that you are accessing
elements in the same column in each iteration of the loop.
Andy
From: Federico Calboli
Charles C. Berry wrote:
Whoa! You are accessing one ROW at a time.
Either way this will tangle up your cache if you have many rows and
columns in your orignal data.
You might do better to do
Y - t( X ) ### use '-' !
for (i in whatever ){
do something using Y[ , i ]
}
My question is NOT how to write the fastest code, it is
whether dummy variables (for lack of better words) make the
memory management better, i.e. faster, or not.
Best,
Fede
--
Federico C. F. Calboli
Department of Epidemiology and Public Health Imperial
College, St Mary's Campus Norfolk Place, London W2 1PG
Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193
f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com
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Re: [R] Reshape (pivot) question
Haven't quite learned to 'cast' yet, but I have always used the 'apply' functions for this type of processing: x - id patient_id date code class eala + ID1564262 1562 6.4.200612:00 1 NA + ID1564262 1562 6.4.200612:00 1 NA + ID1564264 1365 14.2.200614:35 1 50 + ID1564265 1342 7.4.200614:30 2 50 + ID1564266 1648 7.4.200614:30 2 50 + ID1564267 1263 10.2.200615:45 2 10 + ID1564267 1263 10.2.200615:45 3 10 + ID1564269 5646 13.5.200617:02 3 10 + ID1564270 7561 13.5.200617:02 1 10 + ID1564271 1676 15.5.200620:41 2 20 x.in - read.table(textConnection(x), header=TRUE) # 'by' seems to drop NAs so convert to a character string for processing x.in$eala - ifelse(is.na(x.in$eala), NA, as.character(x.in$eala)) # convert date to POSIXlt so we can access the year and month myDate - strptime(x.in$date, %d.%m.%Y%H:%M) x.in$year - myDate$year + 1900 x.in$month - myDate$mon+1 To do this with the reshape package, all you need is: x.in$patient_id - factor(x.in$patient_id) dfm - melt(x.in, id=c(code, month, year), m=c(id,patient_id)) cast(dfm, code + month + year ~ variable, stats) code month year id_n id_uniikit patient_id_n patient_id_uniikit 1 2 20061 11 1 2 4 20062 22 2 3 5 20061 11 1 4 2 20061 11 1 5 5 20061 11 1 6 2 20061 11 1 7 4 20062 12 1 8 5 20061 11 1 Which looks like what you want from your R code, but not your SQL. Hadley __ 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] summary polr
At 15:21 19/02/2007, Paolo Accadia wrote: Hi all, I have a problem to estimate Std. Error and t-value by âpolrâ in library Mass. They result from the summary of a polr object. I can obtain them working in the R environment with the following statements: temp - polr(formula = formula1, data = data1) coeff - summary(temp), but when the above statements are enclosed in a function, summary reports the following error: Error in eval(expr, envir, enclos) : object dat not found Someone knows how I can solve the problem? By giving us a short reproducible example? Specifically we do not know: 1 - what formula1 is 2 - what the structure of data1 is 3 - what the enclosing function looks like 4 - what dat is Thanks for any help. Paolo Michael Dewey http://www.aghmed.fsnet.co.uk __ 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 management uestion [Broadcast]
Liaw, Andy wrote:
I don't see why making copies of the columns you need inside the loop is
better memory management. If the data are in a matrix, accessing
elements is quite fast. If you're worrying about speed of that, do what
Charles suggest: work with the transpose so that you are accessing
elements in the same column in each iteration of the loop.
As I said, this is pretty academic, I am not looking for how to do something
differetly.
Having said that, let me present this code:
for(i in gp){
new[i,1] = ifelse(srow[i]0, new[srow[i],zippo[i]], sav[i])
new[i,2] = ifelse(drow[i]0, new[drow[i],zappo[i]], sav[i])
}
where gp is large vector and srow and drow are the dummy variables for:
srow = data[,2]
drow = data[,4]
If instead of the dummy variable I access the array directly (and its' a 60
x 6 array) the loop takes 2/3 days --not sure here, I killed it after 48 hours.
If I use dummy variables the code runs in 10 minutes-ish.
Comments?
Best,
Fede
--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St Mary's Campus
Norfolk Place, London W2 1PG
Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193
f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com
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Re: [R] Sample size
SAULEAU Erik-André wrote: Dear R-list, I have to design the validation of a score (ordinal values between 0 and 6) reputed to separate 4 groups of patients with known frequencies in the population. I think the more accurate is to calculate sample size under median test. Is there a function for that in R (not in the pwr package)? Thanks in advance, with all my best, erik S. = Erik-André SAULEAU SEAIM Centre Hospitalier 87, Avenue d'Altkirch BP 1070 68051 Mulhouse Cédex Tel: 03 89 64 67 53 Mel: [EMAIL PROTECTED] Web: www.ch-mulhouse.fr The median test has low power and should be avoided. For a validation study a hypothesis test is seldom of interest and you might base the sample size on the needed precision (margin of error; confidence interval width) of some estimate. -- 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] Reading Post-Script files
Hi everybody! Is there any way to read a postscrit file into R? All the best to you Ralf Finne SYH University of Applied Sciences Vasa Finland __ 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] Reshape (pivot) question
Thanks guys! Jim got it right what I was looking for. I think that the reason why I don't get this right with cast-function is that I don't know how to write a proper stats-function. SQL is still much easier for me. Lauri 2007/2/20, hadley wickham [EMAIL PROTECTED]: Haven't quite learned to 'cast' yet, but I have always used the 'apply' functions for this type of processing: x - id patient_id date code class eala + ID1564262 1562 6.4.200612:00 1 NA + ID1564262 1562 6.4.200612:00 1 NA + ID1564264 1365 14.2.200614:35 1 50 + ID1564265 1342 7.4.200614:30 2 50 + ID1564266 1648 7.4.200614:30 2 50 + ID1564267 1263 10.2.200615:45 2 10 + ID1564267 1263 10.2.200615:45 3 10 + ID1564269 5646 13.5.200617:02 3 10 + ID1564270 7561 13.5.200617:02 1 10 + ID1564271 1676 15.5.200620:41 2 20 x.in - read.table(textConnection(x), header=TRUE) # 'by' seems to drop NAs so convert to a character string for processing x.in$eala - ifelse(is.na(x.in$eala), NA, as.character(x.in$eala)) # convert date to POSIXlt so we can access the year and month myDate - strptime(x.in$date, %d.%m.%Y%H:%M) x.in$year - myDate$year + 1900 x.in$month - myDate$mon+1 To do this with the reshape package, all you need is: x.in$patient_id - factor(x.in$patient_id) dfm - melt(x.in, id=c(code, month, year), m=c(id,patient_id)) cast(dfm, code + month + year ~ variable, stats) code month year id_n id_uniikit patient_id_n patient_id_uniikit 1 2 20061 11 1 2 4 20062 22 2 3 5 20061 11 1 4 2 20061 11 1 5 5 20061 11 1 6 2 20061 11 1 7 4 20062 12 1 8 5 20061 11 1 Which looks like what you want from your R code, but not your SQL. Hadley [[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] contextstack overflow
Hello! I written several implementations in R of Rémy's algorithm for generating random ordered strictly binary trees on 2n+1 vertices. One implementation involves manufacturing character strings like: X - list(0,list(0,0)) for the case n=2. If I perform the following two steps: cmd - X - list(0,list(0,0)) eval(parse(text=cmd)) then X becomes a true nested list in R. This works fine for n=2, but often for n=200, an error message: Error in parse(text = cmd) : contextstack overflow appears and execution stops. Clearly there exists an upper bound on the allowable depth of nestings in R! Can this upper bound be easily increased? Other implementations avoid this problem, so this issue is not crucial to me. I do wish, however, to understand the limits of this particular approach. Thank you! Steve Finch http://algo.inria.fr/bsolve/ P.S. If anyone else has written R code for generating random trees (on a fixed number of vertices), I would enjoy seeing this! _ Dont miss your chance to WIN 10 hours of private jet travel from Microsoft® Office Live http://clk.atdmt.com/MRT/go/mcrssaub0540002499mrt/direct/01/ __ 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] contingency table for several variables
DearList, I m trying to draw ONE table that summarize SEVERAL categorical variables according to one classification variable, say sex. The result would look like several contingency tables appended one to the other. All the variables belong to a data frame. The summary.formula in Hmisc package does something pretty close and is ready for a Latex export but I need either to get rid off the percentage (or put the count prior to the percentage )in the reverse option or to add a chisquare test in the response method. The result would look like the one of summary(sex~treatment+Symptoms, fun = table, method = response) in the help of summary.formula but with chisquare tests attached. Or : summary(sex~treatment+Symptoms, fun = table, method = reverse, test= T) gives all the information, but I cant use it for its form is not appropriate. Is there any package where I could find a solution ? Any way to create a function that would add a test in the response method ? Otherwise, ftable should help but I dont know how to use it with a data.frame. Thanks for your help. Regards, David [[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] Installing Package rgl - Compilation Fails
On Mon, 2007-02-19 at 15:11 -0600, Ranjan Maitra wrote: The error is different now. It now cannot find Xext library. Do a yum search on this and install that. yum provides libXext which will give you the package Xext which needs to be installed. You may also need to install the libXext-devel.i386 package. HTH. Ranjan Thanks. Installing libXext-devel allowed rgl to install. Rick B. __ 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] contingency table for several variables
David LEVY wrote: DearList, I ‘m trying to draw ONE table that summarize SEVERAL categorical variables according to one classification variable, say “sex”. The result would look like several contingency tables appended one to the other. All the variables belong to a data frame. The summary.formula in Hmisc package does something pretty close and is ready for a Latex export but I need either to get rid off the percentage (or put the count prior to the percentage )in the “reverse” option or to add a chisquare test in the “response” method. Not a good idea. The % is normalized for sample size differences so should be emphasized. Frank The result would look like the one of summary(sex~treatment+Symptoms, fun = table, method = “response”) in the help of summary.formula but with chisquare tests attached. Or : summary(sex~treatment+Symptoms, fun = table, method = “reverse”, test= T) gives all the information, but I can’t use it for its form is not appropriate. Is there any package where I could find a solution ? Any way to create a function that would add a test in the “response” method ? Otherwise, ftable should help but I don’t know how to use it with a data.frame. Thanks for your help. Regards, David [[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. -- 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.
Re: [R] Installing Package rgl - Compilation Fails
On 2/20/2007 9:44 AM, Rick Bilonick wrote: On Mon, 2007-02-19 at 15:11 -0600, Ranjan Maitra wrote: The error is different now. It now cannot find Xext library. Do a yum search on this and install that. yum provides libXext which will give you the package Xext which needs to be installed. You may also need to install the libXext-devel.i386 package. HTH. Ranjan Thanks. Installing libXext-devel allowed rgl to install. Would you mind summarizing what you started from, and what extras you needed to install? I'd like to add this information to the rgl docs. Duncan Murdoch __ 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] Reading Post-Script files
On Tue, 20 Feb 2007, Ralf Finne wrote: Hi everybody! Is there any way to read a postscrit file into R? See http://www.r-project.org/useR-2006/Slides/Murrell.pdf page 4, the grImport package, now on CRAN, with further notes on Paul Murrell's home page: http://www.stat.auckland.ac.nz/~paul/ All the best to you Ralf Finne SYH University of Applied Sciences Vasa Finland __ 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. -- Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43 e-mail: [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] Reading Post-Script files
On 20-Feb-07 Ralf Finne wrote: Hi everybody! Is there any way to read a postscrit file into R? All the best to you Ralf Finne SYH University of Applied Sciences Vasa Finland Well, yes ... since a PostScript file is ASCII text you could use readline() ... but what you'd do with it after that I cannot imagine! [So I'm joking here] So, to come to the point: Why do you want to do that? If, for example, the PS file displays tabular data which you want to read into R as data, then perhaps one way would be to use suitable utility software to convert the PS file to a PDF file. Then you can display the PDF file using Acrobat Reader, and use the mouse to copy the data into a file which you can then edit up so that it can be read nicely into a dataframe in R. There are also utilities called ps2ascii (part of ghostscript; often fails to do a clean job) and pstotext which you can get from http://www.cs.wisc.edu/~ghost/doc/pstotext.htm (which claims to do a better job, though I've not tested it) which can convert a PS file into an ASCII text file which gives essentially the same text layout as seen when you display/print the PS file. You may then be able to edit this into a form which R can read as you want. But, for better targeted advice, it would be useful to know why you want to read a PDF file into R! Best wishes, Ted. E-Mail: (Ted Harding) [EMAIL PROTECTED] Fax-to-email: +44 (0)870 094 0861 Date: 20-Feb-07 Time: 15:11:34 -- XFMail -- __ 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] summary polr
At 14:41 20/02/2007, you wrote:
Please do not just reply to me,
1 - I might not know
2 - it breaks the threading
Hi
here there is an example extracted from polr help in MASS:
The function could be:
temp - function(form, dat) {
house.plr - polr(formula =
form, weights = Freq, data = dat)
coeff - summary(house.plr)
return(coeff)}
Why do you try to redefine the coeff extractor function?
Try calling the results of summary summ or some
other obvious name and I think you will find the problem goes away.
See also
library(fortunes)
fortune(dog)
Firstly, don't call your matrix 'matrix'. Would you call your dog 'dog'?
Anyway, it might clash with the function 'matrix'.
-- Barry Rowlingson
R-help (October 2004)
the function can be called by:
temp(Sat ~ Infl + Type + Cont, housing)
where all data is available from MASS, as it is
an example in R Help on 'polr'.
Results are:
Re-fitting to get Hessian
Error in eval(expr, envir, enclos) : object dat not found
Paolo Accadia
Michael Dewey [EMAIL PROTECTED] 20/02/07 1:43 PM
At 15:21 19/02/2007, Paolo Accadia wrote:
Hi all,
I have a problem to estimate Std. Error and
t-value by âpolrâ in library Mass.
s.
They result from the summary of a polr object.
I can obtain them working in the R environment
with the following statements:
temp - polr(formula = formula1, data = data1)
coeff - summary(temp),
but when the above statements are enclosed in a
function, summary reports the following error:
Error in eval(expr, envir, enclos) : object dat not found
Someone knows how I can solve the problem?
By giving us a short reproducible example?
Specifically we do not know:
1 - what formula1 is
2 - what the structure of data1 is
3 - what the enclosing function looks like
4 - what dat is
Thanks for any help.
Paolo
Michael Dewey
http://www.aghmed.fsnet.co.uk
Michael Dewey
http://www.aghmed.fsnet.co.uk
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[R] Use R source in .net (R Source in .net einbinden)
Hi! I would like to use an existing R-code in an .net project. Now I realize that there exists a DCOM interface which enables me to use the Statconnector object in my c# project. That way I can get the results of terms using the .evaluate() method. My question is: Is it somehow possible to take a whole file of R code and have it evaluated, or is it possible to sort of compile the R source in a way that it could be called as a method from c# .net (for example compile to dll). It does not seem so, but I thought it couldn't hurt to ask ;-) Maybe someone had a similar problem and could offer me advice. Thanks! Hallo! Ich würde gerne einen existierenden R code in ein .net projekt (C#) einbinden. Übers DCOM Interface und die Evaluate Funktion kann ich ja einzelne Ausdrücke auswerten lassen, aber ist es vielleicht möglich irgendwie ein ganzes code file zu übergeben oder vielleicht aus einem R code eine dll oder ähnliches zu kompilieren, die man dann in C# .net einbinden könnte? Hab dazu nichts gefunden, aber dachte es könnte nicht schaden zu fragen. Vielleicht hat ja jemand schon was in der Art gemacht und kann mir einen Rat geben. Jedenfalls, danke im Voraus! [[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] R: Re: summary polr
Hi all,
The problem is that when you try to use the function summary of a polr object
in a function, it does not work.
The problem is not related to the formula or the structure of data involved.
It is probably related to the use of the function vcov in the code of summary
for polr, and the iterative procedure to estimate the Hessian.
Anyway, here there is an example extracted from polr help in MASS:
The function could be:
temp - function(form, dat) {
house.plr - polr(formula = form, weights = Freq, data = dat)
summ - summary(house.plr)
return(summ)}
the function can be called by:
temp(Sat ~ Infl + Type + Cont, housing)
where all data is available from MASS, as it is an example in R Help on 'polr'.
Results are:
Re-fitting to get Hessian
Error in eval(expr, envir, enclos) : object dat not found
Paolo Accadia
Michael Dewey [EMAIL PROTECTED] 20/02/07 13.43
At 15:21 19/02/2007, Paolo Accadia wrote:
Hi all,
I have a problem to estimate Std. Error and
t-value by “polr†in library Mass.
They result from the summary of a polr object.
I can obtain them working in the R environment with the following statements:
temp - polr(formula = formula1, data = data1)
coeff - summary(temp),
but when the above statements are enclosed in a
function, summary reports the following error:
Error in eval(expr, envir, enclos) : object dat not found
Someone knows how I can solve the problem?
By giving us a short reproducible example?
Specifically we do not know:
1 - what formula1 is
2 - what the structure of data1 is
3 - what the enclosing function looks like
4 - what dat is
Thanks for any help.
Paolo
Michael Dewey
http://www.aghmed.fsnet.co.uk
__
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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] summary polr
That's not it (the function is 'coef' not 'coeff', and R can tell
functions and lists apart).
If you read the help page for polr you will see you could have used
Hess=TRUE. It works then. THAT is why we needed an example, to see how
you used the function.
On Tue, 20 Feb 2007, Michael Dewey wrote:
At 14:41 20/02/2007, you wrote:
Please do not just reply to me,
1 - I might not know
2 - it breaks the threading
Hi
here there is an example extracted from polr help in MASS:
The function could be:
temp - function(form, dat) {
house.plr - polr(formula =
form, weights = Freq, data = dat)
coeff - summary(house.plr)
return(coeff)}
Why do you try to redefine the coeff extractor function?
Try calling the results of summary summ or some
other obvious name and I think you will find the problem goes away.
See also
library(fortunes)
fortune(dog)
Firstly, don't call your matrix 'matrix'. Would you call your dog 'dog'?
Anyway, it might clash with the function 'matrix'.
-- Barry Rowlingson
R-help (October 2004)
the function can be called by:
temp(Sat ~ Infl + Type + Cont, housing)
where all data is available from MASS, as it is
an example in R Help on 'polr'.
Results are:
Re-fitting to get Hessian
Error in eval(expr, envir, enclos) : object dat not found
Paolo Accadia
Michael Dewey [EMAIL PROTECTED] 20/02/07 1:43 PM
At 15:21 19/02/2007, Paolo Accadia wrote:
Hi all,
I have a problem to estimate Std. Error and
t-value by âpolrâ in library Mass.
s.
They result from the summary of a polr object.
I can obtain them working in the R environment
with the following statements:
temp - polr(formula = formula1, data = data1)
coeff - summary(temp),
but when the above statements are enclosed in a
function, summary reports the following error:
Error in eval(expr, envir, enclos) : object dat not found
Someone knows how I can solve the problem?
By giving us a short reproducible example?
Specifically we do not know:
1 - what formula1 is
2 - what the structure of data1 is
3 - what the enclosing function looks like
4 - what dat is
Thanks for any help.
Paolo
Michael Dewey
http://www.aghmed.fsnet.co.uk
Michael Dewey
http://www.aghmed.fsnet.co.uk
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595__
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[R] Mahalanobis distance and probability of group membership using Hotelling's T2 distribution
I want to calculate the probability that a group will include a particular
point using the squared Mahalanobis distance to the centroid. I understand
that the squared Mahalanobis distance is distributed as chi-squared but that
for a small number of random samples from a multivariate normal population
the Hotellings T2 (T squared) distribution should be used.
I cannot find a function for Hotelling's T2 distribution in R (although from
a previous post I have been provided with functions for the Hotelling Test).
My understanding is that the Hotelling's T2 distribution is related to the F
distribution using the equation:
T2(u,v) = F(u, v-u+1)*vu/(v-u+1)
where u is the number of variables and v the number of group members.
I have written the R code below to compare the results from the chi-squared
distribution with the Hotelling's T2 distribution for probability of a
member being included within a group.
Please can anyone confirm whether or not this is the correct way to use
Hotelling's T2 distribution for probability of group membership. Also, when
testing a particular group member, is it preferable to leave that member out
when calculating the centre and covariance of the group for the Mahalanobis
distances?
Thanks
Mike White
## Hotelling T^2 distribution function
ph-function(q, u, v, ...){
# q vector of quantiles as in function pf
# u number of independent variables
# v number of observations
if (!v u+1) stop(n must be greater than p+1)
df1 - u
df2 - v-u+1
pf(q*df2/(v*u), df1, df2, ...)
}
# compare Chi-squared and Hotelling T^2 distributions for a group member
u-3
v-10
set.seed(1)
mat-matrix(rnorm(v*u), nrow=v, ncol=u)
MD2-mahalanobis(mat, center=colMeans(mat), cov=cov(mat))
d-MD2[order(MD2)]
# select a point midway between nearest and furthest from centroid
dm-d[length(d)/2]
1-ph(dm,u,v)# probability using Hotelling T^2 distribution
# [1] 0.6577069
1-pchisq(dm, u) # probability using Chi-squared distribution
# [1] 0.5538466
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[R] Help with xlab and ylab distance from axes
Dear r-helpers, In basic graphics, I have a figure with x and y axes suppresed. I would like to move the xlab and the ylab closer to the axes. Do I have to use mtext()? _ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400Charlottesville, VA 22904-4400 Parcels:Room 102Gilmer Hall McCormick RoadCharlottesville, VA 22903 Office:B011+1-434-982-4729 Lab:B019+1-434-982-4751 Fax:+1-434-982-4766 WWW:http://www.people.virginia.edu/~mk9y/ __ 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] testing slopes
Hello Instead of testing against 0 i would like to test regression slopes against -1. Any idea if there's an R script (package?) available. Thanks for any hint. Cheers Lukas °°° Lukas Indermaur, PhD student eawag / Swiss Federal Institute of Aquatic Science and Technology ECO - Department of Aquatic Ecology Überlandstrasse 133 CH-8600 Dübendorf Switzerland Phone: +41 (0) 71 220 38 25 Fax: +41 (0) 44 823 53 15 Email: [EMAIL PROTECTED] www.lukasindermaur.ch __ 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] summary polr
Thank you very much
Paolo
Prof Brian Ripley [EMAIL PROTECTED] 20/02/07 4:00 PM
That's not it (the function is 'coef' not 'coeff', and R can tell
functions and lists apart).
If you read the help page for polr you will see you could have used
Hess=TRUE. It works then. THAT is why we needed an example, to see how
you used the function.
On Tue, 20 Feb 2007, Michael Dewey wrote:
At 14:41 20/02/2007, you wrote:
Please do not just reply to me,
1 - I might not know
2 - it breaks the threading
Hi
here there is an example extracted from polr help in MASS:
The function could be:
temp - function(form, dat) {
house.plr - polr(formula =
form, weights = Freq, data = dat)
coeff - summary(house.plr)
return(coeff)}
Why do you try to redefine the coeff extractor function?
Try calling the results of summary summ or some
other obvious name and I think you will find the problem goes away.
See also
library(fortunes)
fortune(dog)
Firstly, don't call your matrix 'matrix'. Would you call your dog 'dog'?
Anyway, it might clash with the function 'matrix'.
-- Barry Rowlingson
R-help (October 2004)
the function can be called by:
temp(Sat ~ Infl + Type + Cont, housing)
where all data is available from MASS, as it is
an example in R Help on 'polr'.
Results are:
Re-fitting to get Hessian
Error in eval(expr, envir, enclos) : object dat not found
Paolo Accadia
Michael Dewey [EMAIL PROTECTED] 20/02/07 1:43 PM
At 15:21 19/02/2007, Paolo Accadia wrote:
Hi all,
I have a problem to estimate Std. Error and
t-value by “polr†in library Mass.
s.
They result from the summary of a polr object.
I can obtain them working in the R environment
with the following statements:
temp - polr(formula = formula1, data = data1)
coeff - summary(temp),
but when the above statements are enclosed in a
function, summary reports the following error:
Error in eval(expr, envir, enclos) : object dat not found
Someone knows how I can solve the problem?
By giving us a short reproducible example?
Specifically we do not know:
1 - what formula1 is
2 - what the structure of data1 is
3 - what the enclosing function looks like
4 - what dat is
Thanks for any help.
Paolo
Michael Dewey
http://www.aghmed.fsnet.co.uk
Michael Dewey
http://www.aghmed.fsnet.co.uk
__
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.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Standardized residual variances in SEM
Hello, I'm using the sem package to do a confirmatory factor analysis on data collected with a questionnaire. In the model, there is a unique factor G and 23 items. I would like to calculate the standardized residual variance of the observed variables. Sem only gives the residual variance with the summary function, or the standardized loadings with the standardized.coefficients function (see below). Does anybody know how to standardized the residual variance ? Sincerely yours, summary(semModif.tmp, digits=2) Model Chisquare = 601 Df = 229 Pr(Chisq) = 0 Chisquare (null model) = 2936 Df = 253 Goodness-of-fit index = 0.81 Adjusted goodness-of-fit index = 0.78 RMSEA index = 0.08 90% CI: (0.072, 0.088) Bentler-Bonnett NFI = 0.8 Tucker-Lewis NNFI = 0.85 Bentler CFI = 0.86 BIC = -667 Normalized Residuals Min. 1st Qu. MedianMean 3rd Qu.Max. -2.6300 -0.5640 -0.0728 -0.0067 0.5530 3.5500 Parameter Estimates Estimate Std Error z value Pr(|z|) param1 0.78 0.073 10.70.0e+00 Q1 --- G param2 0.79 0.065 12.10.0e+00 Q2 --- G param3 0.63 0.073 8.50.0e+00 Q3 --- G param4 0.74 0.066 11.20.0e+00 Q4 --- G param6 0.81 0.068 11.90.0e+00 Q6 --- G param7 0.65 0.060 11.00.0e+00 Q7 --- G param9 0.60 0.059 10.10.0e+00 Q9 --- G param10 0.64 0.065 9.90.0e+00 Q10 --- G param11 0.72 0.054 13.30.0e+00 Q11 --- G param12 0.59 0.063 9.30.0e+00 Q12 --- G param13 0.61 0.069 8.70.0e+00 Q13 --- G param14 0.70 0.074 9.60.0e+00 Q14 --- G param15 0.68 0.066 10.40.0e+00 Q15 --- G param16 0.75 0.056 13.30.0e+00 Q16 --- G param17 0.86 0.060 14.30.0e+00 Q17 --- G param18 0.63 0.059 10.70.0e+00 Q18 --- G param19 0.75 0.062 12.20.0e+00 Q19 --- G param20 0.68 0.060 11.40.0e+00 Q20 --- G param21 0.64 0.068 9.30.0e+00 Q21 --- G param22 0.63 0.065 9.70.0e+00 Q22 --- G param23 0.71 0.065 10.90.0e+00 Q23 --- G param24 0.70 0.052 13.70.0e+00 Q24 --- G param25 0.41 0.066 6.33.4e-10 Q25 --- G param26 0.98 0.091 10.80.0e+00 Q1 -- Q1 param27 0.72 0.068 10.60.0e+00 Q2 -- Q2 param28 1.09 0.099 11.00.0e+00 Q3 -- Q3 param29 0.77 0.072 10.70.0e+00 Q4 -- Q4 param31 0.79 0.075 10.60.0e+00 Q6 -- Q6 param32 0.64 0.059 10.70.0e+00 Q7 -- Q7 param34 0.66 0.061 10.80.0e+00 Q9 -- Q9 param35 0.79 0.073 10.80.0e+00 Q10 -- Q10 param36 0.45 0.043 10.40.0e+00 Q11 -- Q11 param37 0.79 0.072 10.90.0e+00 Q12 -- Q12 param38 0.96 0.088 11.00.0e+00 Q13 -- Q13 param39 1.05 0.096 10.90.0e+00 Q14 -- Q14 param40 0.80 0.074 10.80.0e+00 Q15 -- Q15 param41 0.49 0.047 10.40.0e+00 Q16 -- Q16 param42 0.51 0.050 10.10.0e+00 Q17 -- Q17 param43 0.63 0.059 10.80.0e+00 Q18 -- Q18 param44 0.64 0.060 10.60.0e+00 Q19 -- Q19 param45 0.63 0.059 10.70.0e+00 Q20 -- Q20 param46 0.91 0.084 10.90.0e+00 Q21 -- Q21 param47 0.82 0.076 10.90.0e+00 Q22 -- Q22 param48 0.77 0.071 10.80.0e+00 Q23 -- Q23 param49 0.39 0.038 10.30.0e+00 Q24 -- Q24 param50 0.95 0.086 11.10.0e+00 Q25 -- Q25 param51 0.29 0.047 6.34.0e-10 Q9 -- Q7 Iterations = 16 standardized.coefficients(semModif.tmp, digits=2) Std. Estimate param1 param1 0.62 Q1 --- G param2 param2 0.68 Q2 --- G param3 param3 0.51 Q3 --- G param4 param4 0.64 Q4 --- G param6 param6 0.67 Q6 --- G param7 param7 0.63 Q7 --- G param9 param9 0.59 Q9 --- G param10 param10 0.58 Q10 --- G param11 param11 0.73 Q11 --- G param12 param12 0.55 Q12 --- G param13 param13 0.53 Q13 --- G param14 param14 0.57 Q14 --- G param15 param15 0.61 Q15 --- G param16 param16 0.73 Q16 --- G param17 param17 0.77 Q17 --- G param18 param18 0.62 Q18 --- G param19 param19 0.69 Q19 --- G param20 param20 0.65 Q20 --- G param21 param21 0.55 Q21 --- G param22 param22 0.57 Q22 --- G param23 param23 0.63 Q23 --- G param24 param24 0.75 Q24 --- G param25 param25 0.39 Q25 --- G -- Mathieu d'Acremont, PhD [EMAIL PROTECTED] Maître-Assistanttel/fax +4122 379 98 20/44 Pôle de Recherche National en Sciences Affectives CISA - Université de Genève Rue des Battoirs 7 CH-1205 Genève http://affect.unige.ch/ __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide
Re: [R] Help with xlab and ylab distance from axes
On Tue, 2007-02-20 at 11:31 -0500, Michael Kubovy wrote: Dear r-helpers, In basic graphics, I have a figure with x and y axes suppresed. I would like to move the xlab and the ylab closer to the axes. Do I have to use mtext()? Michael, You could set the first value in par(mgp) in the plot() call. Compare: # Default values plot(1, mgp = c(3, 1, 0), axes = FALSE) # Move the labels closer plot(1, mgp = c(1, 1, 0), axes = FALSE) Changing that value is comparable to changing the 'line' argument in mtext(). See ?par HTH, Marc Schwartz __ 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] Installing Package rgl - Compilation Fails - Summary
Summarizing: I'm running R 2.4.1 on a current FC6 32-bit system. In order to have the rgl R package install, I needed to install both mesa-libGLU-devel (FC6 version is 6.5.1-9) and libXext-devel (FC6) rpm packages. Thanks to everyone who commented. Rick B. __ 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] testing slopes
two options are to use an offset term or the linear.hypothesis() function from package car, e.g., y - rnorm(100, 2 - 1 * (x - runif(100, -3, 3)), 3) fit0 - lm(y ~ 1 + offset(-x)) fit1 - lm(y ~ x) anova(fit0, fit1) library(car) linear.hypothesis(fit1, c(x = -1)) I hope it helps. Best, Dimitris Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/(0)16/336899 Fax: +32/(0)16/337015 Web: http://med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm Quoting Indermaur Lukas [EMAIL PROTECTED]: Hello Instead of testing against 0 i would like to test regression slopes against -1. Any idea if there's an R script (package?) available. Thanks for any hint. Cheers Lukas °°° Lukas Indermaur, PhD student eawag / Swiss Federal Institute of Aquatic Science and Technology ECO - Department of Aquatic Ecology Überlandstrasse 133 CH-8600 Dübendorf Switzerland Phone: +41 (0) 71 220 38 25 Fax: +41 (0) 44 823 53 15 Email: [EMAIL PROTECTED] www.lukasindermaur.ch __ 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. Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm __ 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 management uestion [Broadcast]
On Tue, 20 Feb 2007, Federico Calboli wrote:
Liaw, Andy wrote:
I don't see why making copies of the columns you need inside the loop is
better memory management. If the data are in a matrix, accessing
elements is quite fast. If you're worrying about speed of that, do what
Charles suggest: work with the transpose so that you are accessing
elements in the same column in each iteration of the loop.
As I said, this is pretty academic, I am not looking for how to do something
differetly.
Having said that, let me present this code:
for(i in gp){
new[i,1] = ifelse(srow[i]0, new[srow[i],zippo[i]], sav[i])
new[i,2] = ifelse(drow[i]0, new[drow[i],zappo[i]], sav[i])
}
where gp is large vector and srow and drow are the dummy variables for:
srow = data[,2]
drow = data[,4]
If instead of the dummy variable I access the array directly (and its' a
60 x 6 array) the loop takes 2/3 days --not sure here, I killed it after
48 hours.
If I use dummy variables the code runs in 10 minutes-ish.
Comments?
This is a bit different than your original post (where it appeared that
you were manipulating one row of a matrix at a time), but the issue is the
same.
As suggested in my earlier email this looks like a caching issue, and this
is not peculiar to R.
Viz.
Most modern CPUs are so fast that for most program workloads the locality
of reference of memory accesses, and the efficiency of the caching and
memory transfer between different levels of the hierarchy, is the
practical limitation on processing speed. As a result, the CPU spends much
of its time idling, waiting for memory I/O to complete.
(from http://en.wikipedia.org/wiki/Memory_hierarchy)
The computation you have is challenging to your cache, and the effect of
dropping unused columns of your 'data' object by assiging the
columns used to 'srow' and 'drow' has lightened the load.
If you do not know why SAXPY and friends are written as they are, a little
bit of study will be rewarded by a much better understanding of these
issues. I think Golub and Van Loan's 'Matrix Computations' touches on this
(but I do not have my copy close to hand to check).
Best,
Fede
--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St Mary's Campus
Norfolk Place, London W2 1PG
Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193
f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com
Charles C. Berry(858) 534-2098
Dept of Family/Preventive Medicine
E mailto:[EMAIL PROTECTED] UC San Diego
http://biostat.ucsd.edu/~cberry/ La Jolla, San Diego 92093-0901
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Re: [R] memory management uestion [Broadcast]
Charles C. Berry wrote: This is a bit different than your original post (where it appeared that you were manipulating one row of a matrix at a time), but the issue is the same. As suggested in my earlier email this looks like a caching issue, and this is not peculiar to R. Viz. Most modern CPUs are so fast that for most program workloads the locality of reference of memory accesses, and the efficiency of the caching and memory transfer between different levels of the hierarchy, is the practical limitation on processing speed. As a result, the CPU spends much of its time idling, waiting for memory I/O to complete. (from http://en.wikipedia.org/wiki/Memory_hierarchy) The computation you have is challenging to your cache, and the effect of dropping unused columns of your 'data' object by assiging the columns used to 'srow' and 'drow' has lightened the load. If you do not know why SAXPY and friends are written as they are, a little bit of study will be rewarded by a much better understanding of these issues. I think Golub and Van Loan's 'Matrix Computations' touches on this (but I do not have my copy close to hand to check). Thanks for the clarifications. My bottom line is, I prefer dummy variables because they allow me to write cleaner code, with a shorter line for the same instruction i.e. less chances of creeping errors (+ turning into -, etc). I've been challenged that that's memory inefficent, and I wanted to have the opinion of people with more experience than mine on the matter. Best, Fede -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.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] Calculating the Sharpe ratio
Hi Bernd,
It seems to me that the sharpe function uses the diff to calculate the first
differnce of the input which
is a cumalative return series. This is consistant. see sharpe
Basically you need the rate of returns ((priceFinal - Price
Initial)/priceInitial) which you used. In your case r = 0, so you are
calculating the simple signal to noise ratio (mean/std). It looks correct to
me.
The example given in the sharpe function does not seem to be correct though.
data(EuStockMarkets)
dax - log(EuStockMarkets[,DAX])
The input is a time series of closing prices. the simple log does not give a
rate of returns.
you need to use the log Difference of prices to get the returns. and then
divide by std of the return series.
I Hope this helps.
A.
On 2/19/07, Bernd Dittmann [EMAIL PROTECTED] wrote:
Hi useRs,
I am trying to calculate the Sharpe ratio with sharpe of the library
tseries.
The documentation requires the univariate time series to be a
portfolio's cumulated returns. In this case, the example given
data(EuStockMarkets)
dax - log(EuStockMarkets[,FTSE])
is however not the cumulated returns but rather the daily returns of the
FTSE stock index.
Is this way of calculating the Sharpe ratio correct?
Here are my own data:
yearIndexPercentReturns
19851170.091
1986129.90.11
1987149.90.154
1988184.80.233
1989223.10.208
1990223.20
1991220.5-0.012
1992208.1-0.056
1993202.1-0.029
1994203.10.005
1995199.6-0.017
1996208.60.045
1997221.70.063
1998233.70.054
1999250.50.072
2000275.10.098
2001298.60.085
2002350.60.174
2003429.10.224
2004507.60.183
2005536.60.057
2006581.30.083
I calculated the Sharpe ratio in two different ways:
(1) using natural logs as approximation of % returns, using sharpe of
tseries.
(2) using the % returns using a variation the sharpe function.
In both cases I used the risk free rate r=0 and scale=1 since I am using
annual data already.
My results:
METHOD 1: sharpe:
index - log(Index)
sharpe(index, scale=1)
[1] 0.9614212
METHOD 2: my own %-based formula:
mysharp
function(x, r=0, scale=sqrt(250))
{
if (NCOL(x) 1)
stop(x is not a vector or univariate time series)
if (any(is.na(x)))
stop(NAs in x)
if (NROW(x) ==1)
return(NA)
else{
return(scale * (mean(x) - r)/sd(x))
}
}
mysharp(PercentReturns, scale=1)
[1] 0.982531
Both Sharp ratios differ only slightly since logs approximate percentage
changes (returns).
Are both methods correct, esp. since I am NOT using cumulated returns as
the manual says?
If cumulated returns were supposed to be used, could I cumulate the
%-returns with cumsum(PercentReturns)?
Many thanks in advance!
Bernd
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] interaction term and scatterplot3d
Sorry to answer to myself. A solution was trivial with lattice... (as often !) library(lattice) modbusetmp-lm(IKA_buse ~ Ct *Cc,data=dtbuse) G1-cloud(IKA_buse~Ct*Cc,type=h,data=dtbuse) G2-cloud(IKA_buse~Ct*Cc,data=dtbuse) seqCc-seq(min(dtbuse$Cc),max(dtbuse$Cc),l=20) seqCt-seq(min(dtbuse$Ct),max(dtbuse$Ct),l=20) grille-expand.grid(Cc=seqCc,Ct=seqCt) zbuse-predict(modbusetmp,newdata=grille,type=response) G3-wireframe(zbuse~grille$Ct*grille$Cc) print(G3,more=T) print(G1,more=T) print(G2) Some obvious improvements can be done with labels and differencial colors (above or below the surface) can be attributed comparing observations to predicted values at the same x y values... Patrick Giraudoux a écrit : Dear Listers, I would be interested in representing a trend surface including an interaction term z = f(x,y,x.y) - eg the type of chart obtained with persp() or wireframe(), then adding datapoints as a cloud, ideally with dots which are under the surface in a color, and those who are above in another color. An other option would be to draw segments between the dots and the ground of the chart. scatterplot3d looks like being close to do such things except it does not to include (to my knowledge) a coefficient for the interaction term (thus just model z = f(x,y). Does anybody has an idea where to start with this and the main steps? Or a place/website where some script examples can be found? Patrick __ 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] Installing Package rgl - Compilation Fails - Summary
Hi Duncan, I don't know if this will list all the dependencies for your documentation, since Rick's error messages did not involve libraries and header files already installed by him for something else, perhaps. Just a thought. Ranjan On Tue, 20 Feb 2007 11:59:24 -0500 Rick Bilonick [EMAIL PROTECTED] wrote: Summarizing: I'm running R 2.4.1 on a current FC6 32-bit system. In order to have the rgl R package install, I needed to install both mesa-libGLU-devel (FC6 version is 6.5.1-9) and libXext-devel (FC6) rpm packages. Thanks to everyone who commented. Rick B. __ 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] linux gplots install unhappy
Hello all, I use R on both windows and a mainframe linux installation (RedHat enterprise 3.0, which they tell me is soon to be upgraded to 4.0). On windows I installed the package gplots without trouble, and it works fine. When I attempted to do the same on the unix computer, the following error message was forthcoming: downloaded 216Kb * Installing *source* package 'gplots' ... ** R ** data ** inst ** preparing package for lazy loading Loading required package: gtools Warning in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : there is no package called 'gtools' Error: package 'gtools' could not be loaded Execution halted ERROR: lazy loading failed for package 'gplots' ** Removing '/n/fs/disk/resuser02/u/zelickr/R/library/gplots' The downloaded packages are in /tmp/RtmpikM2JW/downloaded_packages Warning messages: 1: installation of package 'gplots' had non-zero exit status in: install.packages(gplots, lib = ~/R/library) 2: cannot create HTML package index in: tools:::unix.packages.html(.Library) Can someone provide the bit of information I need to progress with this? Thanks very much, =Randy= R. Zelick email: [EMAIL PROTECTED] Department of Biology voice: 503-725-3086 Portland State University fax: 503-725-3888 mailing: P.O. Box 751 Portland, OR 97207 shipping: 1719 SW 10th Ave, Room 246 Portland, OR 97201 __ 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] Installing Package rgl - Compilation Fails - Summary
On 2/20/2007 1:11 PM, Ranjan Maitra wrote: Hi Duncan, I don't know if this will list all the dependencies for your documentation, since Rick's error messages did not involve libraries and header files already installed by him for something else, perhaps. No, but it's a start: I'm thinking of something more like a FAQ than comprehensive documentation. Comprehensive docs are not feasible to maintain (there are so many systems that Daniel and I don't use), but hints that two non-standard packages solved one person's problems might be enough of a hint to get someone else going. Duncan Murdoch __ 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] linux gplots install unhappy
install gtools package firstly Aimin At 12:17 PM 2/20/2007, Randy Zelick wrote: gtools' __ 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] linux gplots install unhappy
well, it's complaining because you don't have gtools installed. how about: install.packages(gplots, dep=T) ? b On Feb 20, 2007, at 1:17 PM, Randy Zelick wrote: Hello all, I use R on both windows and a mainframe linux installation (RedHat enterprise 3.0, which they tell me is soon to be upgraded to 4.0). On windows I installed the package gplots without trouble, and it works fine. When I attempted to do the same on the unix computer, the following error message was forthcoming: downloaded 216Kb * Installing *source* package 'gplots' ... ** R ** data ** inst ** preparing package for lazy loading Loading required package: gtools Warning in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : there is no package called 'gtools' Error: package 'gtools' could not be loaded Execution halted ERROR: lazy loading failed for package 'gplots' ** Removing '/n/fs/disk/resuser02/u/zelickr/R/library/gplots' The downloaded packages are in /tmp/RtmpikM2JW/downloaded_packages Warning messages: 1: installation of package 'gplots' had non-zero exit status in: install.packages(gplots, lib = ~/R/library) 2: cannot create HTML package index in: tools:::unix.packages.html(.Library) Can someone provide the bit of information I need to progress with this? Thanks very much, =Randy= R. Zelick email: [EMAIL PROTECTED] Department of Biology voice: 503-725-3086 Portland State University fax: 503-725-3888 mailing: P.O. Box 751 Portland, OR 97207 shipping: 1719 SW 10th Ave, Room 246 Portland, OR 97201 __ 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] baseline fitters
I am pretty pleased with baselines I fit to chromatograms using the
runquantile() function in caTools(v1.6) when its probs parameter is
set to 0.2 and its k parameter to ~1/20th of n (e.g., k ~ 225 for n ~
4500, where n is time series length). This ignores occasional low-
side outliers, and, after baseline subtraction, I can re-adjust any
negative values to zero.
But runquantile's computation time proves exceedingly long for my large
datasets, particularly if I set the endrule parameter to 'func'. Here is
what caTools author Jarek Tuszynski says about relative speeds of various
running-window functions:
- runmin, runmax, runmean run at O(n)
- runmean(..., alg=exact) can have worst case speed of O(n^2) for
some small data vectors, but average case is still close to O(n).
- runquantile and runmad run at O(n*k)
- runmed - related R function runs at O(n*log(k))
The obvious alternative runmin() performs poorly due to dropout (zero-
and low-value 'reverse-spikes') in the data. And runmed fits a baseline that,
upon subtraction, obviously will send half the values into the negative, not
suitable for my application. I jimmied something together
with runmin and runmedian that is considerably faster; unfortunately,
the fit seems less good, at least by eye, due still to the bad runmin
behavior.
I'd be interested in other baseline fitting suggestions implemented
or implementable in R (I'm using v. 2.4.1pat under WinXP). Why, for
instance, can I not find a running trimmean function? Because it
offers no computational savings over runquantile?
Also, the 'func' setting for the caTools endrule parameter--which adjusts the
value of k as ends are approached--is said not to be optimized (using
this option does add further time to computations). Is there an alter-
native that would be speedier, e.g., setting endrule = keep and then
subsequently treating ends with R's smoothEnds() function?
-John Thaden
Little Rock, Arkansas USA
Confidentiality Notice: This e-mail message, including any a...{{dropped}}
__
R-help@stat.math.ethz.ch mailing list
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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] linux gplots install unhappy
On Tue, 2007-02-20 at 10:17 -0800, Randy Zelick wrote: Hello all, I use R on both windows and a mainframe linux installation (RedHat enterprise 3.0, which they tell me is soon to be upgraded to 4.0). On windows I installed the package gplots without trouble, and it works fine. When I attempted to do the same on the unix computer, the following error message was forthcoming: downloaded 216Kb * Installing *source* package 'gplots' ... ** R ** data ** inst ** preparing package for lazy loading Loading required package: gtools Warning in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : there is no package called 'gtools' Error: package 'gtools' could not be loaded Execution halted ERROR: lazy loading failed for package 'gplots' ** Removing '/n/fs/disk/resuser02/u/zelickr/R/library/gplots' The downloaded packages are in /tmp/RtmpikM2JW/downloaded_packages Warning messages: 1: installation of package 'gplots' had non-zero exit status in: install.packages(gplots, lib = ~/R/library) 2: cannot create HTML package index in: tools:::unix.packages.html(.Library) Can someone provide the bit of information I need to progress with this? Thanks very much, =Randy= gplots has a dependency on other packages (gtools and gdata). Thus, when you install it use: install.packages(gplots, dependencies = TRUE, ...) That will download and install the other packages as well. There should have been a similar requirement under Windows, so not sure what may have been different there, unless there is some confounding due to your not installing the packages in standard locations, given some of the output above. I presume that this is because you don't have root access on the Linux server and you are installing to your local user path. HTH, Marc Schwartz __ 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] User defined split function in rpart
I have made some progress with the user defined splitting function and I got
a lot of the things I needed to work. However, I am still stuck on accessing
the node data. It would probably be enough if somebody could tell me, how I
can access the original data frame of the call to rpart.
So if the call is: fit0 - rpart(Sat ~Infl +Cont+ Type,
housing, control=rpart.control(minsplit=10, xval=0),
method=alist)
how can I access the housing data frame within the user defined splitting
function?
Any input would be highly appreciated!
Thank you
Tobias Guennel
-Original Message-
From: Tobias Guennel [mailto:[EMAIL PROTECTED]
Sent: Monday, February 19, 2007 3:40 PM
To: 'r-help@stat.math.ethz.ch'
Subject: [R] User defined split function in rpart
Maybe I should explain my Problem a little bit more detailed.
The rpart package allows for user defined split functions. An example is
given in the source/test directory of the package as usersplits.R.
The comments say that three functions have to be supplied:
1. The 'evaluation' function. Called once per node.
Produce a label (1 or more elements long) for labeling each node,
and a deviance.
2. The split function, where most of the work occurs.
Called once per split variable per node.
3. The init function:
fix up y to deal with offsets
return a dummy parms list
numresp is the number of values produced by the eval routine's label.
I have altered the evaluation function and the split function for my needs.
Within those functions, I need to fit a proportional odds model to the data
of the current node. I am using the polr() routine from the MASS package to
fit the model.
Now my problem is, how can I call the polr() function only with the data of
the current node. That's what I tried so far:
evalfunc - function(y,x,parms,data) {
pomnode-polr(data$y~data$x,data,weights=data$Freq)
parprobs-predict(pomnode,type=probs)
dev-0
K-dim(parprobs)[2]
N-dim(parprobs)[1]/K
for(i in 1:N){
tempsum-0
Ni-0
for(l in 1:K){
Ni-Ni+data$Freq[K*(i-1)+l]
}
for(j in 1:K){
tempsum-tempsum+data$Freq[K*(i-1)+j]/Ni*log(parprobs[i,j]*Ni/data$Freq[K*(i
-1)+j])
}
dev=dev+Ni*tempsum
}
dev=-2*dev
wmean-1
list(label= wmean, deviance=dev)
}
I get the error: Error in eval(expr, envir, enclos) : argument data is
missing, with no default
How can I use the data of the current node?
Thank you
Tobias Guennel
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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] linux gplots install unhappy
On Tue, 20 Feb 2007, Marc Schwartz wrote: On Tue, 2007-02-20 at 10:17 -0800, Randy Zelick wrote: Hello all, I use R on both windows and a mainframe linux installation (RedHat enterprise 3.0, which they tell me is soon to be upgraded to 4.0). On windows I installed the package gplots without trouble, and it works fine. When I attempted to do the same on the unix computer, the following error message was forthcoming: downloaded 216Kb * Installing *source* package 'gplots' ... ** R ** data ** inst ** preparing package for lazy loading Loading required package: gtools Warning in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : there is no package called 'gtools' Error: package 'gtools' could not be loaded Execution halted ERROR: lazy loading failed for package 'gplots' ** Removing '/n/fs/disk/resuser02/u/zelickr/R/library/gplots' The downloaded packages are in /tmp/RtmpikM2JW/downloaded_packages Warning messages: 1: installation of package 'gplots' had non-zero exit status in: install.packages(gplots, lib = ~/R/library) 2: cannot create HTML package index in: tools:::unix.packages.html(.Library) Can someone provide the bit of information I need to progress with this? Thanks very much, =Randy= gplots has a dependency on other packages (gtools and gdata). Thus, when you install it use: install.packages(gplots, dependencies = TRUE, ...) That will download and install the other packages as well. There should have been a similar requirement under Windows, so not sure what may have been different there, unless there is some confounding due You don't need gtools to install a binary package, just to use it! I suspect the menu was used on Windows, where dependencies = TRUE is the default. Come 2.5.0 this sort of query will go away, as the essential dependencies become the default on all platforms. to your not installing the packages in standard locations, given some of the output above. I presume that this is because you don't have root access on the Linux server and you are installing to your local user path. HTH, Marc Schwartz __ 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. -- 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] Installing Package rgl - Compilation Fails - Summary
On Tue, 20 Feb 2007, Ranjan Maitra wrote: Hi Duncan, I don't know if this will list all the dependencies for your documentation, since Rick's error messages did not involve libraries and header files already installed by him for something else, perhaps. It will not, and most of this is already in the README. The problem is the penchant for linux distros to break standard pieces of software into ever smaller pieces, so naming the pieces is often no great help 6 months later. On FC5/6 I think yum install mesa-libGL-devel mesa-libGLU-devel libXext-devel libpng-devel should do it. (Note that mesa-libGL-devel appears to have been already there, and libXext-devel pulls in the rest of the X11 stuff.) A quick check shows -lXext is actually not needed, so it could be removed from configure.ac and the requirements: that would make a lot more sense. Just a thought. Ranjan On Tue, 20 Feb 2007 11:59:24 -0500 Rick Bilonick [EMAIL PROTECTED] wrote: Summarizing: I'm running R 2.4.1 on a current FC6 32-bit system. In order to have the rgl R package install, I needed to install both mesa-libGLU-devel (FC6 version is 6.5.1-9) and libXext-devel (FC6) rpm packages. Thanks to everyone who commented. Rick B. -- 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] baseline fitters
I am not surprised at slowness of runquantile, since it is trying to
perform n=4500 partial sorts of k=225 elements. Here are some thoughts
at speeding it up:
1) playing with different endrule settings can save some time, but
usually results with undesirable effects at first and last 112 values.
All rum* functions in caTools use low level C code for inner elements
between k/2 and n-k/2. However the elements at the edge are calculated
using R functions. In case of runquantile with endrule=func that means
k calls of R quantile function. One option for endrule not available at
present would be to pad both sides of the array with k/2 numbers and
than use endrule=trim. The trick would be to pick good value for the
padding number.
2) you mentioned that you jimmied something together
with runmin and runmedian. I would try something like runmean with
window of size 5, 15, 25 and than runmin with window size k. The first
one should get rid of your 'reverse-spikes' and second would take
running min of your smoothed function.
Best,
Jarek Tuszynski
-Original Message-
From: Thaden, John J [mailto:[EMAIL PROTECTED]
Sent: Tuesday, February 20, 2007 1:23 PM
To: r-help@stat.math.ethz.ch
Cc: Tuszynski, Jaroslaw W.
Subject: baseline fitters
I am pretty pleased with baselines I fit to chromatograms using the
runquantile() function in caTools(v1.6) when its probs parameter is
set to 0.2 and its k parameter to ~1/20th of n (e.g., k ~ 225 for n ~
4500, where n is time series length). This ignores occasional low-
side outliers, and, after baseline subtraction, I can re-adjust any
negative values to zero.
But runquantile's computation time proves exceedingly long for my large
datasets, particularly if I set the endrule parameter to 'func'. Here
is
what caTools author Jarek Tuszynski says about relative speeds of
various
running-window functions:
- runmin, runmax, runmean run at O(n)
- runmean(..., alg=exact) can have worst case speed of O(n^2) for
some small data vectors, but average case is still close to O(n).
- runquantile and runmad run at O(n*k)
- runmed - related R function runs at O(n*log(k))
The obvious alternative runmin() performs poorly due to dropout (zero-
and low-value 'reverse-spikes') in the data. And runmed fits a baseline
that,
upon subtraction, obviously will send half the values into the negative,
not
suitable for my application. I jimmied something together
with runmin and runmedian that is considerably faster; unfortunately,
the fit seems less good, at least by eye, due still to the bad runmin
behavior.
I'd be interested in other baseline fitting suggestions implemented
or implementable in R (I'm using v. 2.4.1pat under WinXP). Why, for
instance, can I not find a running trimmean function? Because it
offers no computational savings over runquantile?
Also, the 'func' setting for the caTools endrule parameter--which
adjusts the
value of k as ends are approached--is said not to be optimized (using
this option does add further time to computations). Is there an alter-
native that would be speedier, e.g., setting endrule = keep and then
subsequently treating ends with R's smoothEnds() function?
-John Thaden
Little Rock, Arkansas USA
Confidentiality Notice: This e-mail message, including any a...{{dropped}}
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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] printing intermediate lines while in a function
Thanks for al the tips, it was the readline() function who did the trick for me, so thanks for all of your input Kind Regards Bart Original message: snip But unfortunately R will do first the calculations and then afterwards return the strings. Is there a way around? __ 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] contextstack overflow
On Tue, 20 Feb 2007, Steven Finch wrote: Hello! I written several implementations in R of Rémy's algorithm for generating random ordered strictly binary trees on 2n+1 vertices. One implementation involves manufacturing character strings like: X - list(0,list(0,0)) for the case n=2. If I perform the following two steps: cmd - X - list(0,list(0,0)) eval(parse(text=cmd)) then X becomes a true nested list in R. This works fine for n=2, but often for n=200, an error message: Error in parse(text = cmd) : contextstack overflow appears and execution stops. Clearly there exists an upper bound on the allowable depth of nestings in R! Can this upper bound be easily increased? It is hardcoded (as 50) in 6 places in gram.c, so fairly easily changed. Other implementations avoid this problem, so this issue is not crucial to me. I do wish, however, to understand the limits of this particular approach. Thank you! Steve Finch http://algo.inria.fr/bsolve/ P.S. If anyone else has written R code for generating random trees (on a fixed number of vertices), I would enjoy seeing this! _ Dont miss your chance to WIN 10 hours of private jet travel from Microsoft® Office Live http://clk.atdmt.com/MRT/go/mcrssaub0540002499mrt/direct/01/ -- 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] linux gplots install unhappy
On Tue, 2007-02-20 at 18:59 +, Prof Brian Ripley wrote: On Tue, 20 Feb 2007, Marc Schwartz wrote: On Tue, 2007-02-20 at 10:17 -0800, Randy Zelick wrote: Hello all, I use R on both windows and a mainframe linux installation (RedHat enterprise 3.0, which they tell me is soon to be upgraded to 4.0). On windows I installed the package gplots without trouble, and it works fine. When I attempted to do the same on the unix computer, the following error message was forthcoming: downloaded 216Kb * Installing *source* package 'gplots' ... ** R ** data ** inst ** preparing package for lazy loading Loading required package: gtools Warning in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : there is no package called 'gtools' Error: package 'gtools' could not be loaded Execution halted ERROR: lazy loading failed for package 'gplots' ** Removing '/n/fs/disk/resuser02/u/zelickr/R/library/gplots' The downloaded packages are in /tmp/RtmpikM2JW/downloaded_packages Warning messages: 1: installation of package 'gplots' had non-zero exit status in: install.packages(gplots, lib = ~/R/library) 2: cannot create HTML package index in: tools:::unix.packages.html(.Library) Can someone provide the bit of information I need to progress with this? Thanks very much, =Randy= gplots has a dependency on other packages (gtools and gdata). Thus, when you install it use: install.packages(gplots, dependencies = TRUE, ...) That will download and install the other packages as well. There should have been a similar requirement under Windows, so not sure what may have been different there, unless there is some confounding due You don't need gtools to install a binary package, just to use it! I suspect the menu was used on Windows, where dependencies = TRUE is the default. Come 2.5.0 this sort of query will go away, as the essential dependencies become the default on all platforms. Thanks for the clarifications. Regards, Marc __ 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] Calculating the Sharpe ratio
Hi Mark,
thanks for your email.
I used your formula for cumul. returns and plugged them into sharpe:
mysharpe - function(x){
+ return(sharpe(cret(x), r=0, scale=1))
+ }
whereby cret is my cumul. returns function as defined by:
cret
function(x){
cumprod(diff(log(x))+1)-1
}
For the index series Index I obtain a sharpe ratio (r=0 and scale=1) of:
mysharpe(Index)
[1] 0.8836429
Do you reckon this result and the method above are correct?
Many thanks in advance!
Bernd
Leeds, Mark (IED) schrieb:
If the doc says to use cumulated and you didn't, then I supsect the call
to shaprp in
Tseries is not correct. Also, to get PercetnREturns, I hope you did
diff(log(series))
Where series is an object containing prices. It's not so clear
Form your email.
If you want to send in cumulative returns ( which
You should do if the doc says to ) you just take the returns ( by doing
above )
and then , add 1 to each element, do a cumprod and then subtract 1 so
something like :
rtns-diff(log(priceseries)
oneplusrtns-1+rtns
cumprodrtns-cumprod(oneplusreturns)
cumrtns-cumprodrtns-1.
Then, the elements in cumrtns represent the cumulative reeturn upto that
point.
But, test it out with an easy example to make sure because I didn't.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Bernd Dittmann
Sent: Monday, February 19, 2007 8:39 AM
To: r-help@stat.math.ethz.ch
Subject: [R] Calculating the Sharpe ratio
Hi useRs,
I am trying to calculate the Sharpe ratio with sharpe of the library
tseries.
The documentation requires the univariate time series to be a
portfolio's cumulated returns. In this case, the example given
data(EuStockMarkets)
dax - log(EuStockMarkets[,FTSE])
is however not the cumulated returns but rather the daily returns of the
FTSE stock index.
Is this way of calculating the Sharpe ratio correct?
Here are my own data:
yearIndexPercentReturns
19851170.091
1986129.90.11
1987149.90.154
1988184.80.233
1989223.10.208
1990223.20
1991220.5-0.012
1992208.1-0.056
1993202.1-0.029
1994203.10.005
1995199.6-0.017
1996208.60.045
1997221.70.063
1998233.70.054
1999250.50.072
2000275.10.098
2001298.60.085
2002350.60.174
2003429.10.224
2004507.60.183
2005536.60.057
2006581.30.083
I calculated the Sharpe ratio in two different ways:
(1) using natural logs as approximation of % returns, using sharpe of
tseries.
(2) using the % returns using a variation the sharpe function.
In both cases I used the risk free rate r=0 and scale=1 since I am using
annual data already.
My results:
METHOD 1: sharpe:
index - log(Index)
sharpe(index, scale=1)
[1] 0.9614212
METHOD 2: my own %-based formula:
mysharp
function(x, r=0, scale=sqrt(250))
{
if (NCOL(x) 1)
stop(x is not a vector or univariate time series) if (any(is.na(x)))
stop(NAs in x) if (NROW(x) ==1)
return(NA)
else{
return(scale * (mean(x) - r)/sd(x))
}
}
mysharp(PercentReturns, scale=1)
[1] 0.982531
Both Sharp ratios differ only slightly since logs approximate percentage
changes (returns).
Are both methods correct, esp. since I am NOT using cumulated returns as
the manual says?
If cumulated returns were supposed to be used, could I cumulate the
%-returns with cumsum(PercentReturns)?
Many thanks in advance!
Bernd
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securities/instruments mentioned or an official confirmation. Morgan Stanley
may deal as principal in or own or act as market maker for
securities/instruments mentioned or may advise the issuers. This is not
research and is not from MS Research but it may refer to a research
analyst/research report. Unless indicated, these views are the author's and
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Re: [R] Installing Package rgl - Compilation Fails - FreeBSD
Duncan Murdoch schrieb: On 2/20/2007 1:11 PM, Ranjan Maitra wrote: Hi Duncan, I don't know if this will list all the dependencies for your documentation, since Rick's error messages did not involve libraries and header files already installed by him for something else, perhaps. No, but it's a start: I'm thinking of something more like a FAQ than comprehensive documentation. Comprehensive docs are not feasible to maintain (there are so many systems that Daniel and I don't use), but hints that two non-standard packages solved one person's problems might be enough of a hint to get someone else going. Duncan, thank you for this purpose. I am such a person who could need some help with installing rgl and hope it is ok to place it in this thread. My trial to install rgl_0.70.tar.gz on R-2.4.1 on FreeBSD 7.0-CURRENT ends up with errors. Obiously something is wrong with Makevars. I have no idea what to do next. 'rgl' is one of the rare cases that do not install under R on FreeBSD. The install messages are short: - #R CMD INSTALL rgl_0.70.tar.gz * Installing to library '/usr/local/lib/R/library' * Installing *source* package 'rgl' ... checking for gcc... gcc checking for C compiler default output file name... a.out checking whether the C compiler works... yes checking whether we are cross compiling... no checking for suffix of executables... checking for suffix of object files... o checking whether we are using the GNU C compiler... yes checking whether gcc accepts -g... yes checking for gcc option to accept ANSI C... none needed checking how to run the C preprocessor... gcc -E checking for X... libraries /usr/X11R6/lib, headers /usr/X11R6/include checking for libpng-config... yes configure: using libpng-config configure: using libpng dynamic linkage configure: creating ./config.status config.status: creating src/Makevars ** libs Makevars, line 9: Need an operator Makevars, line 12: Need an operator Makevars, line 15: Need an operator Makevars, line 21: Need an operator Makevars, line 23: Need an operator Makevars, line 36: Need an operator Makevars, line 38: Need an operator make: fatal errors encountered -- cannot continue chmod: /usr/local/lib/R/library/rgl/libs/*: No such file or directory ERROR: compilation failed for package 'rgl' ** Removing '/usr/local/lib/R/library/rgl' - Are there any experiences with installing rgl on FreeBSD? Do you know if it is at all possible to get rgl to work on FreeBSD? If I can do anything like testing or giving more information let me know. I appreciate any help. Thank you in advance. Rainer Hurling __ 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] Installing Package rgl - Compilation Fails - FreeBSD
The problem is that rgl is apparently written for GNU make, and has (as shipped) ifdef MAKINGAGL [EMAIL PROTECTED]@ -Iext [EMAIL PROTECTED]@ else PKG_CPPFLAGS= -If:/R/R-2.4.1/src/extra/zlib -DHAVE_PNG_H -If:/R/R-2.4.1/src/gnuwin32/bitmap/libpng -Iext PKG_LIBS=-lgdi32 -lopengl32 -lglu32 -Lf:/R/R-2.4.1/src/gnuwin32/bitmap/libpng - lpng -Lf:/R/R-2.4.1/src/extra/zlib -lz endif and similar for BUILDAGL. That seems to have been written to make it workable on MacOS X. Given that configure knows (or could know) the OS, it seems better to write (via configure) a separate Makevars for MacOS X and remove all the ifdef...endif stuff for everyone else. (If you do that in Makevars.in it should work.) On Tue, 20 Feb 2007, Rainer Hurling wrote: Duncan Murdoch schrieb: On 2/20/2007 1:11 PM, Ranjan Maitra wrote: Hi Duncan, I don't know if this will list all the dependencies for your documentation, since Rick's error messages did not involve libraries and header files already installed by him for something else, perhaps. No, but it's a start: I'm thinking of something more like a FAQ than comprehensive documentation. Comprehensive docs are not feasible to maintain (there are so many systems that Daniel and I don't use), but hints that two non-standard packages solved one person's problems might be enough of a hint to get someone else going. Duncan, thank you for this purpose. I am such a person who could need some help with installing rgl and hope it is ok to place it in this thread. My trial to install rgl_0.70.tar.gz on R-2.4.1 on FreeBSD 7.0-CURRENT ends up with errors. Obiously something is wrong with Makevars. I have no idea what to do next. 'rgl' is one of the rare cases that do not install under R on FreeBSD. The install messages are short: - #R CMD INSTALL rgl_0.70.tar.gz * Installing to library '/usr/local/lib/R/library' * Installing *source* package 'rgl' ... checking for gcc... gcc checking for C compiler default output file name... a.out checking whether the C compiler works... yes checking whether we are cross compiling... no checking for suffix of executables... checking for suffix of object files... o checking whether we are using the GNU C compiler... yes checking whether gcc accepts -g... yes checking for gcc option to accept ANSI C... none needed checking how to run the C preprocessor... gcc -E checking for X... libraries /usr/X11R6/lib, headers /usr/X11R6/include checking for libpng-config... yes configure: using libpng-config configure: using libpng dynamic linkage configure: creating ./config.status config.status: creating src/Makevars ** libs Makevars, line 9: Need an operator Makevars, line 12: Need an operator Makevars, line 15: Need an operator Makevars, line 21: Need an operator Makevars, line 23: Need an operator Makevars, line 36: Need an operator Makevars, line 38: Need an operator make: fatal errors encountered -- cannot continue chmod: /usr/local/lib/R/library/rgl/libs/*: No such file or directory ERROR: compilation failed for package 'rgl' ** Removing '/usr/local/lib/R/library/rgl' - Are there any experiences with installing rgl on FreeBSD? Do you know if it is at all possible to get rgl to work on FreeBSD? If I can do anything like testing or giving more information let me know. I appreciate any help. Thank you in advance. Rainer Hurling __ 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. -- 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.
[R] analysis of correlation matrices
Hello, I'm looking for a package in R that performs, analysis of correlation matrices: cross-classified by 2 factors. The orginal reference to this method is by CJ Brien Biometrica (1998) 75(3):469-76. THank you, Agnes - E. Agnes Richards, Ph.D. Candidate Department of Zoology University of Toronto at Mississauga 3359 Mississauga Rd. North Mississauga, Ont. Canada L5L 1C6 lab 905-828-5452 fax 905-828-3792 __ 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] Simplification of Generalised Linear mixed effects models using glmmPQL
Hello Tom, the problem is because R has assumed that pop and rep are integers, not factor levels. Try: test - read.table(test.txt,header=T) sapply(test, class) test$pop - factor(test$pop) test$rep - factor(test$rep) then try fitting the models. Also, there has been substantial discussion about the production of p-values for mixed-effects models in R; it's now a FAQ: http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-are-p_002dvalues-not-displayed-when-using-lmer_0028_0029_003f The package writer (Professor Bates) recommends the use of mcmcsamp to obtain inferential information about your model - see ?mcmcsamp in the lme4 package for examples of its use. Cheers, Andrew ps it's a bad idea to call things data :) On Tue, Feb 20, 2007 at 01:13:25PM +, T.C. Cameron wrote: Dear R users I have built several glmm models using glmmPQL in the following structure: m1-glmmPQL(dev~env*har*treat+dens, random = ~1|pop/rep, family = Gamma) (full script below, data attached) I have tried all the methods I can find to obtain some sort of model fit score or to compare between models using following the deletion of terms (i.e. AIC, logLik, anova.lme(m1,m2)), but I cannot get any of them to work. Yet I see on several R help pages that others have with similar models? I have tried the functions in lme4 as well and lmer or lmer2 will not accept my random terms of rep (replicate) nested within pop population. I have read the appropriate sections of the available books and R help pages but I am at a loss of where to move from here data-read.table(D:\\bgytcc\\MITES\\Data\\Analysis\\test.txt,header=T) attach(data) names(data) m1-glmmPQL(dev~env*har*treat+dens, random = ~1|pop/rep, family = Gamma) summary(m1) anova.lme(m1) m2-update(m1,~.-env:har:treat) anova.lme(m1,m2)###this does not work AIC(m1)##this does not work logLik(m1)##this does not work? ##this does not work class(m1) - lme class(m2) - lme anova.lme(m1,m2) # m3-lmer(dev~env*har*treat+dens + (1|pop/rep), family = Gamma) ## this generates an error Error in lmerFactorList(formula, mf, fltype) : number of levels in grouping factor(s) 'rep:pop', 'pop' is too large In addition: Warning messages: 1: numerical expression has 1851 elements: only the first used in: rep:pop 2: numerical expression has 1851 elements: only the first used in: rep:pop m4-lmer(dev~env*har*treat + dens + (1|rep) +(1|pop), family = Gamma, method = Laplace) ## this works but it does not give me an anova output with p values anova(m4) Analysis of Variance Table Df Sum Sq Mean Sq env1 17858 17858 har2 879 439 treat 226131306 dens 1 1016476 1016476 env:har2 870 435 env:treat 21188 594 har:treat 4 313 78 env:har:treat 41188 297 Dr Tom C Cameron Genetics, Ecology and Evolution IICB, University of Leeds Leeds, UK Office: +44 (0)113 343 2837 Lab:+44 (0)113 343 2854 Fax:+44 (0)113 343 2835 Email: [EMAIL PROTECTED] Webpage: click here http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/ __ 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] Installing Package rgl - Compilation Fails - FreeBSD
On 2/20/2007 4:45 PM, Prof Brian Ripley wrote: The problem is that rgl is apparently written for GNU make, and has (as shipped) ifdef MAKINGAGL [EMAIL PROTECTED]@ -Iext [EMAIL PROTECTED]@ else PKG_CPPFLAGS= -If:/R/R-2.4.1/src/extra/zlib -DHAVE_PNG_H -If:/R/R-2.4.1/src/gnuwin32/bitmap/libpng -Iext PKG_LIBS=-lgdi32 -lopengl32 -lglu32 -Lf:/R/R-2.4.1/src/gnuwin32/bitmap/libpng - lpng -Lf:/R/R-2.4.1/src/extra/zlib -lz endif and similar for BUILDAGL. That seems to have been written to make it workable on MacOS X. Given that configure knows (or could know) the OS, it seems better to write (via configure) a separate Makevars for MacOS X and remove all the ifdef...endif stuff for everyone else. (If you do that in Makevars.in it should work.) On MacOS X we currently build two libraries, one for X11 and one for AGL, and these tests choose between those two targets (which need different compilation of a few files, and separate linking of all files against different libraries). Fixing this to work more portably isn't something that I know how to do. If someone wants to fix it and send me a patch I'll incorporate it, but otherwise it likely won't get fixed. By the way, the file you quote is Makevars, which shouldn't have been shipped: it gets produced from Makevars.in. I'll have to be careful to do the packaging from a clean checkout next time. Duncan Murdoch __ 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] Different gridlines per panel in xyplot
In the example R script below, horizontal gray gridlines are drawn at y
coordinates where the points are drawn with the code:
panel.abline(h=y, v=xScale, col.line=gray)
How do I change this so that the horizontal gray gridlines are drawn at y
coordinates where the y labels are drawn? The challenge is that each panel
has different y-ranges (in my real example the y-ranges and y-intervals are
even more different). For example, I wish I could use the yScale list as the
h parameter in abline, but it does not work with a list.
Thanks for any help.
Rene
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
panel.abline(h=y, v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
__
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] Different gridlines per panel in xyplot
Am 20 Feb 2007 um 20:52 hat Rene Braeckman geschrieben:
From: Rene Braeckman [EMAIL PROTECTED]
To: r-help@stat.math.ethz.ch
Date sent: Tue, 20 Feb 2007 20:52:29 -0800
Subject:[R] Different gridlines per panel in xyplot
In the example R script below, horizontal gray gridlines are drawn at
y coordinates where the points are drawn with the code:
panel.abline(h=y, v=xScale, col.line=gray)
How do I change this so that the horizontal gray gridlines are drawn
at y coordinates where the y labels are drawn? The challenge is that
each panel has different y-ranges (in my real example the y-ranges and
y-intervals are even more different). For example, I wish I could use
the yScale list as the h parameter in abline, but it does not work
with a list.
Thanks for any help.
Rene
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
panel.abline(h=y, v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
Dear Rene,
I am not quite sure whether this is the most elegant/general
solution, but one option might be to use trunc(), see the full code
below.
panel.abline(h=trunc(y), v=xScale, col.line=gray)
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
## use trunc(y)
panel.abline(h=trunc(y), v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
HTH,
Bernd
__
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] Different gridlines per panel in xyplot
Thanks for the reply. Trunc would only work when the truncated y values
result in the desired y coordinates for the grid lines as in this simple
data set. Since my real dataset contains many more points, it does not give
a general solution.
Rene
-Original Message-
From: Bernd Weiss [mailto:[EMAIL PROTECTED]
Sent: Tuesday, February 20, 2007 9:44 PM
To: Rene Braeckman; r-help@stat.math.ethz.ch
Subject: Re: [R] Different gridlines per panel in xyplot
Am 20 Feb 2007 um 20:52 hat Rene Braeckman geschrieben:
From: Rene Braeckman [EMAIL PROTECTED]
To: r-help@stat.math.ethz.ch
Date sent: Tue, 20 Feb 2007 20:52:29 -0800
Subject:[R] Different gridlines per panel in xyplot
In the example R script below, horizontal gray gridlines are drawn at
y coordinates where the points are drawn with the code:
panel.abline(h=y, v=xScale, col.line=gray)
How do I change this so that the horizontal gray gridlines are drawn
at y coordinates where the y labels are drawn? The challenge is that
each panel has different y-ranges (in my real example the y-ranges and
y-intervals are even more different). For example, I wish I could use
the yScale list as the h parameter in abline, but it does not work
with a list.
Thanks for any help.
Rene
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
panel.abline(h=y, v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
Dear Rene,
I am not quite sure whether this is the most elegant/general solution, but
one option might be to use trunc(), see the full code below.
panel.abline(h=trunc(y), v=xScale, col.line=gray)
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
## use trunc(y)
panel.abline(h=trunc(y), v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
HTH,
Bernd
__
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] Different gridlines per panel in xyplot
I solved my own problem. Suddenly remembered the list of very useful
functions under Accessing Auxiliary Information During Plotting in the
help pages.
Here is the line that did the trick:
panel.abline(h=yScale[[panel.number()]], v=xScale, col.line=gray)
Rene
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Rene Braeckman
Sent: Tuesday, February 20, 2007 8:52 PM
To: r-help@stat.math.ethz.ch
Subject: [R] Different gridlines per panel in xyplot
In the example R script below, horizontal gray gridlines are drawn at y
coordinates where the points are drawn with the code:
panel.abline(h=y, v=xScale, col.line=gray)
How do I change this so that the horizontal gray gridlines are drawn at y
coordinates where the y labels are drawn? The challenge is that each panel
has different y-ranges (in my real example the y-ranges and y-intervals are
even more different). For example, I wish I could use the yScale list as the
h parameter in abline, but it does not work with a list.
Thanks for any help.
Rene
library(lattice)
Subj - rep(1:4,each=3)
Time - rep(1:3,4) + 0.1
Conc - (1:12) + 0.1
df - data.frame(Subj,Time,Conc)
xScale - 1:3
yScale - list(1:3,4:6,7:9,10:12)
xyplot(Conc ~ Time | Subj,
data = df,
layout = c(2,2),
type=b,
scales=list(
x=list(at=xScale),
y=list(at=yScale,relation=free)
),
panel = function(x,y,...) {
panel.abline(h=y, v=xScale, col.line=gray)
panel.xyplot(x,y,...)
}
)
__
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] Splom plot:how to plot with different symbols?
Hi, Kindly let me know if I posted a wrong question in the forum. I want to draw a splom plot with different symbols in plot. My command is as follows: splom(~ log10(splomData[2:3]), groups = programs, data = splomData, panel = panel.superpose, key = list(title = paste(splomLoop,Programs of Hog Analysis (Sorted by LR(GB))), panel = panel.superpose, columns = splomLoop, points = list(pch = c(1:splomLoop), #this will display different symbols in legend but not in actual graph col = rainbow(splomLoop, s=1, v=1), text = trim(as.character(ProgramNameList[1:splomLoop,1]) Kindly help. Thanks Regards Sarthi M. [[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.
