Re: [R] fitting truncated normal distribution
Sorry, that I forgot an example.
I have demand-data which is either 0 or a positive value.
When I have an article which is not ordered very often, it could look
like this:
x=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1280,0,0,0,0,640,0,0
,0,0,0,0,0,0,0)
library(MASS) ## for fitdistr
library(msm) ## for dtnorm
dtnorm0 - function(x, mean = 0, sd = 1, log = FALSE) {
dtnorm(x, mean, sd, 0, Inf, log)
}
fitdistr(x,dtnorm0,start=list(mean=0,sd=1))
Unfortunately I get the same error message.
I found a function, that works for a weibull distribution and tried to
apply it but it didn't work neither
# truncated weibull distribution
#dweibull.trunc -
#function(x, shape, scale=1, trunc.=Inf, log=FALSE){
#ln.dens - (dweibull(x, shape, scale, log=TRUE)
#-pweibull(trunc., shape, scale = 1, lower.tail = TRUE, log.p =
#TRUE))
#if(any(oops - (xtrunc.)))
#ln.dens[oops] - (-Inf)
#if(log)ln.dens else exp(ln.dens)
#}
#
#x - rweibull(100, 1)
#range(x)
#x4 - x[x=4]
#fitdistr(x4, dweibull.trunc, start=list(shape=1, scale=1), trunc=4)
# truncated normal distribution
dtnorm0 - function(x, mean, sd, a=0, log = FALSE) {
ln.dens - (dnorm(x, mean, sd)
- pnorm(a, mean, sd, lower.tail=TRUE, log.p =TRUE))
if(any(oops - (xa)))
ln.dens[oops] - (-Inf)
if(log)ln.dens else exp(ln.dens)
}
fitdistr(x, dtnorm0, start = list(mean = 0, sd = 1))
Maybe, when I alter mean and sd, I get an answer, which is not really
satisfactory. I hope, there is a solution possible
And thank you in advance
markus
Sorry, didn't notice that you *did* mention dtnorm is part of msm.
Ignore that part of the advice...
--sundar
Sundar Dorai-Raj wrote:
[EMAIL PROTECTED] wrote:
Hello,
I am a new user of R and found the function dtnorm() in the package
msm.
My problem now is, that it is not possible for me to get the mean and
sd out of a sample when I want a left-truncated normal distribution
starting at 0.
fitdistr(x,dtnorm, start=list(mean=0, sd=1))
returns the error message
Fehler in [-(`*tmp*`, x = lower x = upper, value = numeric(0))
:nichts zu ersetzen
I don't know, where to enter the lower/upper value. Is there a
possibility to program the dtnorm function by myself?
Thank you very much in advance for your help, markus
---
Versendet durch aonWebmail (webmail.aon.at)
__
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.
Hi, Markus,
You should always supply the package name where dtnorm is located. My
guess is most don't know (as I didn't) it is part of the msm package.
Also, you should supply a reproducible example so others may
understand your particular problem. For example, when I ran your code
on data generated from rtnorm (also part of msm) I got warnings
related to the NaNs generated in pnorm and qnorm, but no error as you
reported. Both of these suggestions are in the posting guide (see
signature above).
So, to answer your problem, here's a quick example.
library(MASS) ## for fitdistr
library(msm) ## for dtnorm
dtnorm0 - function(x, mean = 0, sd = 1, log = FALSE) {
dtnorm(x, mean, sd, 0, Inf, log)
}
set.seed(1) ## to others may reproduce my results exactly x -
rtnorm(100, lower = 0) fitdistr(x, dtnorm0, start = list(mean = 0, sd
= 1))
Note, the help page ?fitdistr suggests additional parameters may be
passed to the density function (i.e. dtnorm) or optim. However, this
won't work here because lower is an argument for both functions.
This is the reason for writing dtnorm0 which has neither a lower or an
upper argument.
HTH,
--sundar
__
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.
[[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] Setting contrasts for polr() to get same result of SAS
T Mu muster at gmail.com writes: Hi all, I am trying to do a ordered probit regression using polr(), replicating a result from SAS. polr(y ~ x, dat, method='probit') suppose the model is y ~ x, where y is a factor with 3 levels and x is a factor with 5 levels, To get coefficients, SAS by default use the last level as reference, R by default use the first level (correct me if I was wrong), Yes. I tried relevel, reorder, contrasts, but no success. I found what really matters is I am sure those can help but you need to be carefull to reorder levels that the order is the same in SAS and R. options(contrasts = c(contr.treatment, contr.poly)) or options(contrasts = c(contr.SAS, contr.poly)) You can also set contrasts directly to factors via contrasts(x) - contr.SAS where x is your factor. You can also set different contrasts to different factors. Gregor __ 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] help about agnes
Arnau == Arnau Mir Torres [EMAIL PROTECTED] on Wed, 16 Aug 2006 19:38:27 +0200 writes: Arnau Hello. Arnau I have the following distance matrix between 8 points: Arnau [1,] 0.00 3.162278 7.280110 8.544004 7.071068 9.899495 6.403124 8.062258 Arnau [2,] 3.162278 0.00 5.00 6.403124 4.472136 8.944272 6.082763 8.062258 [ .. ] Arnau So, can somebody say me what do these numbers represent? I would have helped you if you had followed the last two lines below Arnau Thanks in advance, Arnau Arnau. __ 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. ^ these I mean ^ __ 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] nls convergence problem
nls not converging for zero-noise cases Setzer.Woodrow at epamail.epa.gov writes: No doubt Doug Bates would gladly accept patches ... . The zero-noise case is irrlevant in practice, but quite often I have uttered /(!! (vituperation filter on) when nls did not converge with real data. The dreaded min step reduced And yet, I found that nls is damned right not to behave nicely in many cases. Recently, a colleague fitted gastric emptying curves using GraphPad, with 100% success, and nls failed for one third of these. When we checked GraphPads output more closely, some of the coefficients looked like 2.1 with a confidence interval in the range -27128 ... 314141. Nobody forces you to look at these, though, when using GraphPad. I only wish nls were a little bit more polite in telling me what went wrong. Dieter __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] separate row averages for different parts of an array
The following reshapes mat so we can take the means of the columns of the resulting 3d array and then transposes it back to the original orientation: t(colMeans(array(t(mat), c(100, 448, 24 You might want to try it on this test set first where anscombe is an 11x8 data set built into R. Here are 4 solutions using anscombe 1. This is just the above written for the anscombe data set: t(colMeans(array(t(anscombe), c(4,2,11 2. Here is a solution using apply instead of colMeans and t. In this case anscombe is a data.frame, not an array/matrix, and we need to turn it into one first. The prior solution also required a matrix but tranpose will convert a dataframe to a matrix so we did not have to explicitly do it there. If your array is indeed an array as stated in your post then you can omit the as.matrix part. In your case the c(11,4,2) vector would be c(24, 100, 448) : apply(array(as.matrix(anscombe), c(11,4,2)), c(1,3), mean) 3. Here is another solution. This one uses the zoo package and does have the advantage of not having to specify a bunch of dimensions. It uses rapply from zoo (which will be renamed rollapply in the next version of zoo so as not to conflict with the new rapply that is appearing in R 2.4.0). In your case both occurrences of 4 would be 100: library(zoo) coredata(t(rapply(zoo(t(anscombe)), 4, by = 4, mean))) 4. This is Marc's solution except we use seq instead of : at the end in order to make use of the length= argument. In your case c(11, 8, 4) would be c(1, 44800, 100) and length = 4 would be length = 100: sapply(seq(1, 8, 4), function(i) rowMeans(anscombe[, seq(i, length = 4)])) On 8/16/06, Spencer Jones [EMAIL PROTECTED] wrote: I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Problem with the special argument '...' within a function
Hans-Joerg Bibiko wrote:
Dear all,
I wrote some functions using the special argument '...'. OK, it works.
But if I call such a function which also called such a function, then
I get an error message about unused arguments.
Here's an example:
fun1 - function(x,a=1)
{
print(paste(x=,x))
print(paste(a=,a))
}
fun2 - function(y,b=2)
{
print(paste(y=,y))
print(paste(b=,b))
}
myfun - function(c, ...)
{
print(paste(c=,c))
fun1(x=c,...)
fun2(y=c,...)
}
This is OK.
myfun(c=3)
[1] c= 3
[1] x= 3
[1] a= 1
[1] y= 3
[1] b= 2
myfun(c=3,a=4)
[1] c= 3
[1] x= 3
[1] a= 4
Error in fun2(y = c, ...) : unused argument(s) (a ...)
I understand the error message because fun2 has no argument called 'a'.
But how can I avoid this???
Try Ben Bolker's clean.args in the plotrix package
myfun(clean.args(list(c=3,a=4),myfun))
[1] c= 3 c= 4
[1] x= 3 x= 4
[1] a= 1
[1] y= 3 y= 4
[1] b= 2
Jim
__
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] day, month, year functions
Gregor == Gregor Gorjanc [EMAIL PROTECTED] on Fri, 11 Aug 2006 00:27:27 + (UTC) writes: Gregor Gabor Grothendieck ggrothendieck at gmail.com writes: Here are three ways: xx - as.Date(2006-01-05) # 1. use as.POSIXlt as.POSIXlt(xx)$mday as.POSIXlt(xx)$mon + 1 as.POSIXlt(xx)$year + 1900 # 2. use format as.numeric(format(xx, %d)) as.numeric(format(xx, %m)) as.numeric(format(xx, %Y)) # 3. use month.day.year in chron package library(chron) month.day.year(unclass(xx))$day month.day.year(unclass(xx))$month month.day.year(unclass(xx))$year Gregor Hi, Gregor it would really be great if there would be Gregor sec(), min(), hour() day(), month(), year() Gregor generic functions that would work on all date classes. Where Gregor applicable of course. I imagine that argument to get out integer Gregor or character would alse be nice. I disagree pretty strongly: - We definitely don't want min() to return minutes instead of minimum ! - Why pollute the namespace with 6 (well, actualy 5!) new function names, when as.POSIXlt() *REALLY* is there exactly for this purpose ??? I rather think the authors of each of the other old-fashioned date classes should provide as.POSIXlt() methods for their classes. Then, we'd have uniform interfaces, following's Gabor's # 1. above. Martin Maechler, ETH Zurich __ 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] day, month, year functions
Martin Maechler wrote: Gregor == Gregor Gorjanc [EMAIL PROTECTED] on Fri, 11 Aug 2006 00:27:27 + (UTC) writes: Gregor Gabor Grothendieck ggrothendieck at gmail.com writes: Here are three ways: xx - as.Date(2006-01-05) # 1. use as.POSIXlt as.POSIXlt(xx)$mday as.POSIXlt(xx)$mon + 1 as.POSIXlt(xx)$year + 1900 # 2. use format as.numeric(format(xx, %d)) as.numeric(format(xx, %m)) as.numeric(format(xx, %Y)) # 3. use month.day.year in chron package library(chron) month.day.year(unclass(xx))$day month.day.year(unclass(xx))$month month.day.year(unclass(xx))$year Gregor Hi, Gregor it would really be great if there would be Gregor sec(), min(), hour() day(), month(), year() Gregor generic functions that would work on all date classes. Where Gregor applicable of course. I imagine that argument to get out integer Gregor or character would alse be nice. I disagree pretty strongly: - We definitely don't want min() to return minutes instead of minimum ! Pheu, a good catch. You are definitely right! - Why pollute the namespace with 6 (well, actualy 5!) new function names, when as.POSIXlt() *REALLY* is there exactly for this purpose ??? I rather think the authors of each of the other old-fashioned date classes should provide as.POSIXlt() methods for their classes. Then, we'd have uniform interfaces, following's Gabor's # 1. above. My proposal above was just a direction to a common way of dealing with dates within R. If as.POSIXlt() methods is the way, that is perfectly fine with me. -- Lep pozdrav / With regards, Gregor Gorjanc -- University of Ljubljana PhD student Biotechnical Faculty Zootechnical Department URI: http://www.bfro.uni-lj.si/MR/ggorjan Groblje 3 mail: gregor.gorjanc at bfro.uni-lj.si SI-1230 Domzale tel: +386 (0)1 72 17 861 Slovenia, Europefax: +386 (0)1 72 17 888 -- One must learn by doing the thing; for though you think you know it, you have no certainty until you try. Sophocles ~ 450 B.C. __ 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] rpvm/snow packages on a cluster with dual-processor machi nes
Dear Paul,
(I forgot to answer over the weekend). With mpi it is essentially the same.
When using makeCluster, specify the number of slaves. If you have three
machines, and you want each to run two slave processes, just use a 6.
Before that, though, you should tell LAM/MPI how to set up the lam universe.
The simplest way is to specify that in a configuration file for LAM. Put
something like this (using appropriate IPs or host names; cpu=xx indicates
that you want each physical node to run those many xx slaves; it might, or
might not, be related to the actual number of CPUs) in a file called, say,
lamb-conf1.def
192.168.2.2 cpu=2
192.168.2.3 cpu=2
192.168.2.4 cpu=2
Now do (as user, NOT root)
lamboot -v lamb-conf1.def
If that works, then start R, and use snow.
A very good explanation on how to use mpi with R appeared in R news a while
ago by the author of Rmpi.
HTH,
R.
On Monday 14 August 2006 16:17, Liaw, Andy wrote:
That's what I've tried before, on three dual-Xeon boxes, so I know it
worked (as documented a that time).
Andy
From: Paul Y. Peng
Luke Tierney just reminded me that makeCluster() can take a
number greater than the number of machines in a cluster. It
seems to be a solution to this problem. But I haven't tested it yet.
Paul.
Ryan Austin wrote:
Hi,
Adding a node twice gives a duplicate node error.
However, adding the parameter sp=2000 to your pvm hostfile should
enable dual processors.
Ryan
Liaw, Andy wrote:
Caveat: I've only played with this a couple of years ago...
I believe you can just add each host _twice_ (or as many
times as the
number of CPUs at that host) to get both CPUs to work.
Andy
From: Paul Y. Peng
Hi,
does anybody know how to use the dual processors in the
machines of
a cluster? I am using R with rpvm and snow packages. I
usually start
pvm daemon and add host machines first, and then run R to
start my
computing work. But I find that only one processor in
each machine
is used in this way and the other one always stays idle. Is there
any simple way to tell pvm to use the two processors at the same
time? In other words, I would like to see two copies of R
running on
each machine's two processors when using pvm. Any hints/help are
greatly appreciated.
Paul.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
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.
--
Ramón Díaz-Uriarte
Bioinformatics
Centro Nacional de Investigaciones Oncológicas (CNIO)
(Spanish National Cancer Center)
Melchor Fernández Almagro, 3
28029 Madrid (Spain)
Fax: +-34-91-224-6972
Phone: +-34-91-224-6900
http://ligarto.org/rdiaz
PGP KeyID: 0xE89B3462
(http://ligarto.org/rdiaz/0xE89B3462.asc)
**NOTA DE CONFIDENCIALIDAD** Este correo electrónico, y en s...{{dropped}}
__
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] tkinser
Dear list, I 'd like to know if it is possible to delete my text window after running it?? I have add a Menu to my text window and so i can for example open a script; then i run it and i have my result on my R console. But i'd like that after running, the code disappears automatically. i d'like something that clean my text window. I have a second problem: My text window and all my widgets are not fixed: I use combo box, message box...and it always moves, it appears on the right of my screen, on the bottom..or on the bar tasks. I d'like my text window not move at all and after if it's possible that my widgets appear on the same place on my sreen. When they appear on the bottom on my tasks bar, i have to open it each time... Thanks a lot. Julie. Cet été, pensez aux cartes postales de laposte.net ! [[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] NLME: Limitations of using identify to interact with scatterplots?
I have a quick question regarding the use of identify to interact with points on a scatterplot. My question is essentially: can identify be used when one is plotting model objects to generate diagnostic plots? Specifically I am using NLME. For example, I am plotting the fitted values on the x axis vs a variable called log2game with the following code: plot(D2C29.nlme, log2game ~ fitted(.), abline=c(0,1)) and then I have tried to use identify as follows: identify(D2C29.nlme$fitted[,2],Data2$log2game,row.names(Data2)) (if I leave out the [,2] on the fitted attributes then I am told that x and y are not the same length and it appears that this is due to the fact that the fitted attribute has 2 columns.) but I get an error message that plot.new has not been called yet. I am not sure if this is because I am doing something wrong or if identify simply cannot be used in this context. Many thanks Greg __ 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] glmmPQL question!
Will this do? best, Simon ## simulate some data... set.seed(1) joint - c(rep(1,20),rep(2,20),rep(3,20)) time - runif(60)+1 subject - factor(rep(1:12,rep(5,12))) mu - time*joint joint - factor(joint) y - rgamma(mu,mu) ## fit model b - glmmPQL(y~joint*time,random=~1|subject,family=Gamma(link=identity)) ## extract fixed effect parameter estimates and covariance matrix fix.b - b$coefficients$fixed V.b - b$varFix ## Create a `prediction matrix' pd - data.frame(time = rep(seq(1,2,length=100),3), joint=factor(c(rep(1,100),rep(2,100),rep(3,100 Xp - model.matrix(~joint*time,pd) ## use it to get predictions and associated standard errors mu - Xp %*% fix.b mu.se - diag(Xp%*%V.b%*%t(Xp))^.5 ## inefficient for readability ## check this is done right range(mu - predict(b,pd,level=0)) ## produce plot plot(pd$time[1:100],mu[1:100],main=joint==1,type=l) lines(pd$time[1:100],mu[1:100]+2*mu.se[1:100],lty=2) lines(pd$time[1:100],mu[1:100]-2*mu.se[1:100],lty=3) [EMAIL PROTECTED] wrote: Hello Folks- Is there a way to create confidence bands with 'glmmPQL' ??? I am performing a stroke study for Northwestern University in Chicago, Illinois. I am trying to decide a way to best plot the model which we created with the glmmPQL function in R. I would like to plot my actual averaged data points within 95 % confidence intervals from the model. Plotting the model is easy, but determining confidence bands is not. Here is my model: ratiomodel-glmmPQL(ratio~as.factor(joint)*time, random = ~ 1 | subject, family = Gamma(link = identity),alldata3) I am used to seeing confidence intervals from models that increase, “flair out” in the y direction, at the beginning and ending time points (x values) of the simulated data. If I use 'lm' and pass the command 'int = c ' 'to create this model I can easily find and plot this type of confidence band for 'ratio~time'. But I need to take into account 'as.factor(joint)', and in fact I can produce confidence bands with 'glm' by passing in 'se.fit = TRUE', but the problem is I need to make subject a random variable, and take into account my ratio with the Gamma distribution. Is there a way to create confidence bands with 'glmmPQL' ??? ' as.factor(joint)' has 3 levels, so I would like to produce this linear model with three levels and confidence bands for comparison of the levels of 'joint'. Any Help at all with my problem would be greatly appreciated!! LJ __ 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. -- Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK +44 1225 386603 www.maths.bath.ac.uk/~sw283 __ 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] Specifying Path Model in SEM for CFA
On Wed, 2006-08-16 at 17:01 -0400, John Fox wrote: Dear Rick, It's unclear to me what you mean by constraining each column of the factor matrix to sum to one. If you intend to constrain the loadings on each factor to sum to one, sem() won't do that, since it supports only equality constraints, not general linear constraints on parameters of the model, but why such a constraint would be reasonable in the first place escapes me. More common in confirmatory factor analysis would be to constrain more of the loadings to zero. Of course, one would do this only if it made substantive sense in the context of the research. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox I'm trying to build a multivariate receptor model as described by Christensen and Sain (Technometrics, vol 44 (4) pp. 328-337). The model is x_t = Af_t + e_t where A is the matrix of nonnegative source compositions, x_t are the observed pollutant concentrations at time t, and f_t are the unobserved factors. The columns of A are supposed to sum to no more than 100%. They say they are using a latent variable model. If sem can't handle this, do you know of another R package that could? 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] tkinser
Dear Julie, -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of julie7.josse Sent: Thursday, August 17, 2006 4:01 AM To: r-help Subject: [R] tkinser Importance: High Dear list, I 'd like to know if it is possible to delete my text window after running it?? I have add a Menu to my text window and so i can for example open a script; then i run it and i have my result on my R console. But i'd like that after running, the code disappears automatically. i d'like something that clean my text window. I think that what you mean is that you'd like to delete the text in the window rather than the window itself. If the text widget is called txt, then you can do tkdelete(txt, 0.0, end) I have a second problem: My text window and all my widgets are not fixed: I use combo box, message box...and it always moves, it appears on the right of my screen, on the bottom..or on the bar tasks. I d'like my text window not move at all and after if it's possible that my widgets appear on the same place on my sreen. When they appear on the bottom on my tasks bar, i have to open it each time... If the top-level Tk window is named top, then, after creating the window, e.g., tkwm.geometry(tt, -100+100) will position it 100 pixels 100 pixels from the right top corner of the display. More generally, I found it useful to read Welch, Jones, and Hobbs, Practical Programming in Tcl and Tk, to learn these kinds of things. I hope this helps, John Thanks a lot. Julie. Cet iti, pensez aux cartes postales de laposte.net ! [[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] Specifying Path Model in SEM for CFA
Dear Rick, -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Rick Bilonick Sent: Thursday, August 17, 2006 7:07 AM To: John Fox Cc: 'R Help'; 'Rick Bilonick' Subject: Re: [R] Specifying Path Model in SEM for CFA . . . I'm trying to build a multivariate receptor model as described by Christensen and Sain (Technometrics, vol 44 (4) pp. 328-337). The model is x_t = Af_t + e_t where A is the matrix of nonnegative source compositions, x_t are the observed pollutant concentrations at time t, and f_t are the unobserved factors. The columns of A are supposed to sum to no more than 100%. They say they are using a latent variable model. If sem can't handle this, do you know of another R package that could? sem() handles only equality constraints among parameters, and this model requires linear inequality constraints. I'm aware of SEM software that handles inequality constraints, but I'm not aware of anything in R that will do it out of the box. One possibility is to write out the likelihood (or fitting function) for your model and perform a bounded optimization using optim(). It would probably be a fair amount of work setting up the problem. Finally, there are tricks that permit the imposition of general constraints and inequality constraints using software, like sem(), that handles only equality constraints. It's probably possible to do what you want using such a trick, but it would be awkward. See the references given in Bollen, Structural Equations with Latent Variables (Wiley, 1989), pp. 401-403. I'm sorry that I can't be of more direct help. John __ 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] Plots Without Displaying
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Thank you, It seems that a list of plots is just possible using lattice plots. But that's a good keyword for me to look for, I appreciate your help! Lothar Christos Hatzis wrote: Yes, you can do that for lattice-based plots. The functions in the lattice package produce objects of class trellis which can be stored in a list and processed or updated at a later time: library(lattice) attach(barley) plotList - list(length=3) plotList[[1]] - xyplot(yield ~ site, data=barley) plotList[[2]] - xyplot(yield ~ variety, data=barley) plotList[[3]] - xyplot(yield ~ year, data=barley) plotList plotList[[3]] - update(plotList[[3]], yaxis=Yield (bushels/acre)) print(plotList[[3]]) Obviously, you can store any lattice-based plot in the list. HTH. -Christos Christos Hatzis, Ph.D. Nuvera Biosciences, Inc. 400 West Cummings Park Suite 5350 Woburn, MA 01801 Tel: 781-938-3830 www.nuverabio.com -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Lothar Botelho-Machado Sent: Wednesday, August 16, 2006 4:49 PM To: r-help@stat.math.ethz.ch Subject: Re: [R] Plots Without Displaying Prof Brian Ripley wrote: Yes, see ?jpeg ?bitmap and as you didn't tell us your OS we don't know if these are available to you. jpeg(file=test.jpg) boxplot(sample(100)) dev.off() may well work. 'An Introduction to R' explains about graphics devices, including these. On Wed, 16 Aug 2006, Lothar Botelho-Machado wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 R Help Mailing List, I'd like to generate a plot that I could display and/or store it as e.g. jpeg. But unfortunately always a plotting window opens. Is it possible to prevent that? I tried the following: R bp-boxplot( sample(100), plot=FALSE) This works somehow, but it only stores data (as discribed in the help) in bp and it is not possible afaik to display bp later on or store them as a jpeg. The next: R p-plot(sample(100), sample(100), plot=FALSE) ..and also a variant using jpeg() didn't work at all. Is there a way to generally store the plots as object, without displaying them, or perhaps directly saving them to disc as jpeg? A Yes or No or any further help/links are appreciated!!! Thank you for the explanation and your patience in answering me this obviously very simple question!! Originally I tried to store plots directly in a list. So writing them directly to disc was just a good alternative. I knew that that jpeg() provides functionality for that, but didn't use it correctly. Hence, is it also possible to store a plot in a list, somehow? Kind regards, Lothar __ 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. -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.3 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFE5HU1HRf7N9c+X7sRAguEAJ4855nuonJaB9VXHkGOr/SZhqow8wCfXcuB o8oqpYoJ7MXgnVtnuGAE5Yk= =ZWgN -END PGP SIGNATURE- __ 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] NLME: Limitations of using identify to interact with scatterplots?
Most plotting functions in the nlme package use lattice graphics functions based on the grid package. Identify will not work with lattice graphics. I'm not sure if there is a replacement. On 8/17/06, Greg Distiller [EMAIL PROTECTED] wrote: I have a quick question regarding the use of identify to interact with points on a scatterplot. My question is essentially: can identify be used when one is plotting model objects to generate diagnostic plots? Specifically I am using NLME. For example, I am plotting the fitted values on the x axis vs a variable called log2game with the following code: plot(D2C29.nlme, log2game ~ fitted(.), abline=c(0,1)) and then I have tried to use identify as follows: identify(D2C29.nlme$fitted[,2],Data2$log2game,row.names(Data2)) (if I leave out the [,2] on the fitted attributes then I am told that x and y are not the same length and it appears that this is due to the fact that the fitted attribute has 2 columns.) but I get an error message that plot.new has not been called yet. I am not sure if this is because I am doing something wrong or if identify simply cannot be used in this context. Many thanks Greg __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Plots Without Displaying
Also check out the displaylist: http://tolstoy.newcastle.edu.au/R/help/04/05/0817.html On 8/17/06, Lothar Botelho-Machado [EMAIL PROTECTED] wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Thank you, It seems that a list of plots is just possible using lattice plots. But that's a good keyword for me to look for, I appreciate your help! Lothar Christos Hatzis wrote: Yes, you can do that for lattice-based plots. The functions in the lattice package produce objects of class trellis which can be stored in a list and processed or updated at a later time: library(lattice) attach(barley) plotList - list(length=3) plotList[[1]] - xyplot(yield ~ site, data=barley) plotList[[2]] - xyplot(yield ~ variety, data=barley) plotList[[3]] - xyplot(yield ~ year, data=barley) plotList plotList[[3]] - update(plotList[[3]], yaxis=Yield (bushels/acre)) print(plotList[[3]]) Obviously, you can store any lattice-based plot in the list. HTH. -Christos Christos Hatzis, Ph.D. Nuvera Biosciences, Inc. 400 West Cummings Park Suite 5350 Woburn, MA 01801 Tel: 781-938-3830 www.nuverabio.com -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Lothar Botelho-Machado Sent: Wednesday, August 16, 2006 4:49 PM To: r-help@stat.math.ethz.ch Subject: Re: [R] Plots Without Displaying Prof Brian Ripley wrote: Yes, see ?jpeg ?bitmap and as you didn't tell us your OS we don't know if these are available to you. jpeg(file=test.jpg) boxplot(sample(100)) dev.off() may well work. 'An Introduction to R' explains about graphics devices, including these. On Wed, 16 Aug 2006, Lothar Botelho-Machado wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 R Help Mailing List, I'd like to generate a plot that I could display and/or store it as e.g. jpeg. But unfortunately always a plotting window opens. Is it possible to prevent that? I tried the following: R bp-boxplot( sample(100), plot=FALSE) This works somehow, but it only stores data (as discribed in the help) in bp and it is not possible afaik to display bp later on or store them as a jpeg. The next: R p-plot(sample(100), sample(100), plot=FALSE) ..and also a variant using jpeg() didn't work at all. Is there a way to generally store the plots as object, without displaying them, or perhaps directly saving them to disc as jpeg? A Yes or No or any further help/links are appreciated!!! Thank you for the explanation and your patience in answering me this obviously very simple question!! Originally I tried to store plots directly in a list. So writing them directly to disc was just a good alternative. I knew that that jpeg() provides functionality for that, but didn't use it correctly. Hence, is it also possible to store a plot in a list, somehow? Kind regards, Lothar __ 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. -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.3 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFE5HU1HRf7N9c+X7sRAguEAJ4855nuonJaB9VXHkGOr/SZhqow8wCfXcuB o8oqpYoJ7MXgnVtnuGAE5Yk= =ZWgN -END PGP SIGNATURE- __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] fitting truncated normal distribution
Hi, Markus,
Are these always integers? Why do you think they should be normal or
Weibull? Seems more like a mixture with a point mass at 0 and something
else (e.g. Poisson, negative binomial, normal). Though it's hard to tell
with what you have provided. If that's the case you'll have to write
your own likelihood function or, if they are integers, use zip
(zero-inflated Poisson) or zinb (zero-inflated negative binomial). Do an
RSiteSearch to find many packages will do these fits.
RSiteSearch(zero-inflated)
Again, this is pure speculation based on your x below alone and no
other information (I'm not sure what demand-data means).
HTH,
--sundar
Schweitzer, Markus wrote:
Sorry, that I forgot an example.
I have demand-data which is either 0 or a positive value.
When I have an article which is not ordered very often, it could look
like this:
x=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1280,0,0,0,0,640,0,0
,0,0,0,0,0,0,0)
library(MASS) ## for fitdistr
library(msm) ## for dtnorm
dtnorm0 - function(x, mean = 0, sd = 1, log = FALSE) {
dtnorm(x, mean, sd, 0, Inf, log)
}
fitdistr(x,dtnorm0,start=list(mean=0,sd=1))
Unfortunately I get the same error message.
I found a function, that works for a weibull distribution and tried to
apply it but it didn't work neither
# truncated weibull distribution
#dweibull.trunc -
#function(x, shape, scale=1, trunc.=Inf, log=FALSE){
#ln.dens - (dweibull(x, shape, scale, log=TRUE)
#-pweibull(trunc., shape, scale = 1, lower.tail = TRUE, log.p =
#TRUE))
#if(any(oops - (xtrunc.)))
#ln.dens[oops] - (-Inf)
#if(log)ln.dens else exp(ln.dens)
#}
#
#x - rweibull(100, 1)
#range(x)
#x4 - x[x=4]
#fitdistr(x4, dweibull.trunc, start=list(shape=1, scale=1), trunc=4)
# truncated normal distribution
dtnorm0 - function(x, mean, sd, a=0, log = FALSE) {
ln.dens - (dnorm(x, mean, sd)
- pnorm(a, mean, sd, lower.tail=TRUE, log.p =TRUE))
if(any(oops - (xa)))
ln.dens[oops] - (-Inf)
if(log)ln.dens else exp(ln.dens)
}
fitdistr(x, dtnorm0, start = list(mean = 0, sd = 1))
Maybe, when I alter mean and sd, I get an answer, which is not really
satisfactory. I hope, there is a solution possible
And thank you in advance
markus
Sorry, didn't notice that you *did* mention dtnorm is part of msm.
Ignore that part of the advice...
--sundar
Sundar Dorai-Raj wrote:
[EMAIL PROTECTED] wrote:
Hello,
I am a new user of R and found the function dtnorm() in the package
msm.
My problem now is, that it is not possible for me to get the mean and
sd out of a sample when I want a left-truncated normal distribution
starting at 0.
fitdistr(x,dtnorm, start=list(mean=0, sd=1))
returns the error message
Fehler in [-(`*tmp*`, x = lower x = upper, value = numeric(0))
:nichts zu ersetzen
I don't know, where to enter the lower/upper value. Is there a
possibility to program the dtnorm function by myself?
Thank you very much in advance for your help, markus
---
Versendet durch aonWebmail (webmail.aon.at)
__
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.
Hi, Markus,
You should always supply the package name where dtnorm is located. My
guess is most don't know (as I didn't) it is part of the msm package.
Also, you should supply a reproducible example so others may
understand your particular problem. For example, when I ran your code
on data generated from rtnorm (also part of msm) I got warnings
related to the NaNs generated in pnorm and qnorm, but no error as you
reported. Both of these suggestions are in the posting guide (see
signature above).
So, to answer your problem, here's a quick example.
library(MASS) ## for fitdistr
library(msm) ## for dtnorm
dtnorm0 - function(x, mean = 0, sd = 1, log = FALSE) {
dtnorm(x, mean, sd, 0, Inf, log)
}
set.seed(1) ## to others may reproduce my results exactly x -
rtnorm(100, lower = 0) fitdistr(x, dtnorm0, start = list(mean = 0, sd
= 1))
Note, the help page ?fitdistr suggests additional parameters may be
passed to the density function (i.e. dtnorm) or optim. However, this
won't work here because lower is an argument for both functions.
This is the reason for writing dtnorm0 which has neither a lower or an
upper argument.
HTH,
--sundar
__
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] Plots Without Displaying
On Thu, 17 Aug 2006, Lothar Botelho-Machado wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Thank you, It seems that a list of plots is just possible using lattice plots. But that's a good keyword for me to look for, I appreciate your help! Actually, that is not a list of *plots*. The objects stored there are more sets of instructions to the print method of what to plot, and you can do that for any type of plot. It is possible to store low-level descriptions of plots and replay them: see recordPlot and replayPlot. BUT, it is preferable to run the expressions to create the plot on the new device. Christos Hatzis wrote: Yes, you can do that for lattice-based plots. The functions in the lattice package produce objects of class trellis which can be stored in a list and processed or updated at a later time: library(lattice) attach(barley) plotList - list(length=3) plotList[[1]] - xyplot(yield ~ site, data=barley) plotList[[2]] - xyplot(yield ~ variety, data=barley) plotList[[3]] - xyplot(yield ~ year, data=barley) plotList plotList[[3]] - update(plotList[[3]], yaxis=Yield (bushels/acre)) print(plotList[[3]]) Obviously, you can store any lattice-based plot in the list. HTH. -Christos Christos Hatzis, Ph.D. Nuvera Biosciences, Inc. 400 West Cummings Park Suite 5350 Woburn, MA 01801 Tel: 781-938-3830 www.nuverabio.com -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Lothar Botelho-Machado Sent: Wednesday, August 16, 2006 4:49 PM To: r-help@stat.math.ethz.ch Subject: Re: [R] Plots Without Displaying Prof Brian Ripley wrote: Yes, see ?jpeg ?bitmap and as you didn't tell us your OS we don't know if these are available to you. jpeg(file=test.jpg) boxplot(sample(100)) dev.off() may well work. 'An Introduction to R' explains about graphics devices, including these. On Wed, 16 Aug 2006, Lothar Botelho-Machado wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 R Help Mailing List, I'd like to generate a plot that I could display and/or store it as e.g. jpeg. But unfortunately always a plotting window opens. Is it possible to prevent that? I tried the following: R bp-boxplot( sample(100), plot=FALSE) This works somehow, but it only stores data (as discribed in the help) in bp and it is not possible afaik to display bp later on or store them as a jpeg. The next: R p-plot(sample(100), sample(100), plot=FALSE) ..and also a variant using jpeg() didn't work at all. Is there a way to generally store the plots as object, without displaying them, or perhaps directly saving them to disc as jpeg? A Yes or No or any further help/links are appreciated!!! Thank you for the explanation and your patience in answering me this obviously very simple question!! Originally I tried to store plots directly in a list. So writing them directly to disc was just a good alternative. I knew that that jpeg() provides functionality for that, but didn't use it correctly. Hence, is it also possible to store a plot in a list, somehow? Kind regards, Lothar __ 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. -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.3 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFE5HU1HRf7N9c+X7sRAguEAJ4855nuonJaB9VXHkGOr/SZhqow8wCfXcuB o8oqpYoJ7MXgnVtnuGAE5Yk= =ZWgN -END PGP SIGNATURE- __ 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] Variance Components in R
Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ..., ch06.R, ch08.R, containing the R scripts described in the book. These R script files make it much easier and more enjoyable to study that book, because they make it much easier to try the commands described in the book, one line at a time, testing modifications to check you comprehension, etc. In addition to avoiding problems with typographical errors, it also automatically overcomes a few minor but substantive changes in the notation between S-Plus and R. Also, the MINQUE method has been obsolete for over 25 years. I recommend you use method = REML except for when you want to compare two nested models with different fixed effects; in that case, you should use method = ML, as explained in Pinheiro and Bates (2000). Hope this helps. Spencer Graves Iuri Gavronski wrote: Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = REML /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. Thank you for your help. Best regards, Iuri. ___ Iuri Gavronski - [EMAIL PROTECTED] doutorando UFRGS/PPGA/NITEC - www.ppga.ufrgs.br Brazil __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Variance Components in R
Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data? -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski Sent: Thursday, August 17, 2006 11:08 AM To: Spencer Graves Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Variance Components in R Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ..., ch06.R, ch08.R, containing the R scripts described in the book. These R script files make it much easier and more enjoyable to study that book, because they make it much easier to try the commands described in the book, one line at a time, testing modifications to check you comprehension, etc. In addition to avoiding problems with typographical errors, it also automatically overcomes a few minor but substantive changes in the notation between S-Plus and R. Also, the MINQUE method has been obsolete for over 25 years. I recommend you use method = REML except for when you want to compare two nested models with different fixed effects; in that case, you should use method = ML, as explained in Pinheiro and Bates (2000). Hope this helps. Spencer Graves Iuri Gavronski wrote: Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = REML /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. Thank you for your help. Best regards, Iuri. ___ Iuri Gavronski - [EMAIL PROTECTED] doutorando UFRGS/PPGA/NITEC - www.ppga.ufrgs.br Brazil __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]]
Re: [R] Variance Components in R
This will (should) be a piece of cake for lmer. But, I don't speak SPSS.
Can you write your model out as a linear model and give a brief
description of the data and your problem?
In addition to what Spencer noted as help below, you should also check
out the vignette in the mlmRev package. This will give you many
examples.
vignette('MlmSoftRev')
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf
Of Iuri Gavronski
Sent: Thursday, August 17, 2006 11:16 AM
To: Doran, Harold
Subject: Re: [R] Variance Components in R
9500 records. It didn`t run in SPSS or SAS on Windows machines,
so I am trying to convert the SPSS script to R to run in a RISC station
at the university.
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
Iuri:
The lmer function is optimal for large data with crossed
random effects.
How large are your data?
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of
Iuri Gavronski
Sent: Thursday, August 17, 2006 11:08 AM
To: Spencer Graves
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Variance Components in R
Thank you for your reply.
VARCOMP is available at SPSS advanced models, I'm not
sure
for how long it exists... I only work with SPSS for
the last
4 years...
My model only has crossed random effects, what perhaps
would
drive me to lmer().
However, as I have unbalanced data (why it is normally
called
'unbalanced design'? the data was not intended to be
unbalanced, only I could not get responses for all
cells...),
I'm afraid that REML would take too much CPU, memory
and time
to execute, and MINQUE would be faster and provide
similar
variance estimates (please, correct me if I'm wrong on
that point).
I only found MINQUE on the maanova package, but as my
study
is very far from genetics, I'm not sure I can use this
package.
Any comment would be appreciated.
Iuri
On 8/16/06, Spencer Graves [EMAIL PROTECTED]
wrote:
I used SPSS over 25 years ago, but I don't
recall
ever fitting a
variance components model with it. Are all your
random
effects nested?
If they were, I would recommend you use 'lme' in the
'nlme' package.
However, if you have crossed random effects, I
suggest you
try 'lmer'
associated with the 'lme4' package.
For 'lmer', documentation is available in
Douglas
Bates. Fitting
linear mixed models in R. /R News/, 5(1):27-30, May
2005
(www.r-project.org - newsletter). I also recommend
you try the
vignette available with the 'mlmRev' package (see,
e.g.,
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html).
Excellent documentation for both 'lme' (and
indirectly for
'lmer') is available in Pinheiro and Bates (2000)
Mixed-Effects Models
in S and S-Plus (Springer). I have personally
recommended
this book
so many times on this listserve that I just now got
234 hits for
RSiteSearch(graves pinheiro). Please don't
hesitate to pass this
recommendation to your university library. This
book is
the primary
documentation for the 'nlme' package, which is part
of the
standard R
distribution. A subdirectory
~library\nlme\scripts of your R
installation includes files named ch01.R,
ch02.R, ...,
ch06.R,
ch08.R, containing the R scripts described in the
book. These R
script files make it much easier and more enjoyable
to study that
book, because they make it much easier to try the
commands
described
in the book, one line at a time, testing
modifications to check you
comprehension, etc. In addition to avoiding
problems with
typographical errors, it also automatically
overcomes a few
minor but
substantive changes in the notation between S-Plus
and R.
[R] Fwd: Variance Components in R
9500 records. It didn`t run in SPSS or SAS on Windows machines, so I am trying to convert the SPSS script to R to run in a RISC station at the university. On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote: Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data? -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski Sent: Thursday, August 17, 2006 11:08 AM To: Spencer Graves Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Variance Components in R Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ..., ch06.R, ch08.R, containing the R scripts described in the book. These R script files make it much easier and more enjoyable to study that book, because they make it much easier to try the commands described in the book, one line at a time, testing modifications to check you comprehension, etc. In addition to avoiding problems with typographical errors, it also automatically overcomes a few minor but substantive changes in the notation between S-Plus and R. Also, the MINQUE method has been obsolete for over 25 years. I recommend you use method = REML except for when you want to compare two nested models with different fixed effects; in that case, you should use method = ML, as explained in Pinheiro and Bates (2000). Hope this helps. Spencer Graves Iuri Gavronski wrote: Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = REML /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. Thank you for your help. Best regards, Iuri. ___ Iuri Gavronski - [EMAIL PROTECTED] doutorando UFRGS/PPGA/NITEC - www.ppga.ufrgs.br Brazil __ R-help@stat.math.ethz.ch mailing list
Re: [R] Specifying Path Model in SEM for CFA
sem() handles only equality constraints among parameters, and this model requires linear inequality constraints. I'm aware of SEM software that handles inequality constraints, but I'm not aware of anything in R that will do it out of the box. One possibility is to write out the likelihood (or fitting function) for your model and perform a bounded optimization using optim(). It would probably be a fair amount of work setting up the problem. Finally, there are tricks that permit the imposition of general constraints and inequality constraints using software, like sem(), that handles only equality constraints. It's probably possible to do what you want using such a trick, but it would be awkward. See the references given in Bollen, Structural Equations with Latent Variables (Wiley, 1989), pp. 401-403. I'm sorry that I can't be of more direct help. John Thanks. I'll explore the options you mention. I would like to use R because I need to couple this with block bootstrapping to handle time dependencies. Rick __ 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] Plots Without Displaying
Yes, you can do that for lattice-based plots. The functions in the lattice package produce objects of class trellis which can be stored in a list and processed or updated at a later time: Or for ggplot based plots: install.packages(ggplot) library(ggplot) plotList - list(length=3) plotList[[1]] - qplot(yield, site, data=barley) plotList[[2]] - qplot(yield, variety, data=barley) plotList[[3]] - qplot(yield, year, data=barley) Which actually stores plot objects which are independent of their representation as graphics. 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] Variance Components in R
Hi, Iuri:
If you've got an 8086 AND a huge data set, compute time might be a
problem with 'lmer'. However, if you a reasonably modern computer and
only a a few thousand observations, 'lmer' should complete almost in the
blink of an eye -- or at least in less time than it would talk for a cup
of coffee.
Spencer
Doran, Harold wrote:
This will (should) be a piece of cake for lmer. But, I don't speak SPSS.
Can you write your model out as a linear model and give a brief
description of the data and your problem?
In addition to what Spencer noted as help below, you should also check
out the vignette in the mlmRev package. This will give you many
examples.
vignette('MlmSoftRev')
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf
Of Iuri Gavronski
Sent: Thursday, August 17, 2006 11:16 AM
To: Doran, Harold
Subject: Re: [R] Variance Components in R
9500 records. It didn`t run in SPSS or SAS on Windows machines,
so I am trying to convert the SPSS script to R to run in a RISC station
at the university.
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
Iuri:
The lmer function is optimal for large data with crossed
random effects.
How large are your data?
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of
Iuri Gavronski
Sent: Thursday, August 17, 2006 11:08 AM
To: Spencer Graves
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Variance Components in R
Thank you for your reply.
VARCOMP is available at SPSS advanced models, I'm not
sure
for how long it exists... I only work with SPSS for
the last
4 years...
My model only has crossed random effects, what perhaps
would
drive me to lmer().
However, as I have unbalanced data (why it is normally
called
'unbalanced design'? the data was not intended to be
unbalanced, only I could not get responses for all
cells...),
I'm afraid that REML would take too much CPU, memory
and time
to execute, and MINQUE would be faster and provide
similar
variance estimates (please, correct me if I'm wrong on
that point).
I only found MINQUE on the maanova package, but as my
study
is very far from genetics, I'm not sure I can use this
package.
Any comment would be appreciated.
Iuri
On 8/16/06, Spencer Graves [EMAIL PROTECTED]
wrote:
I used SPSS over 25 years ago, but I don't
recall
ever fitting a
variance components model with it. Are all your
random
effects nested?
If they were, I would recommend you use 'lme' in the
'nlme' package.
However, if you have crossed random effects, I
suggest you
try 'lmer'
associated with the 'lme4' package.
For 'lmer', documentation is available in
Douglas
Bates. Fitting
linear mixed models in R. /R News/, 5(1):27-30, May
2005
(www.r-project.org - newsletter). I also recommend
you try the
vignette available with the 'mlmRev' package (see,
e.g.,
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html).
Excellent documentation for both 'lme' (and
indirectly for
'lmer') is available in Pinheiro and Bates (2000)
Mixed-Effects Models
in S and S-Plus (Springer). I have personally
recommended
this book
so many times on this listserve that I just now got
234 hits for
RSiteSearch(graves pinheiro). Please don't
hesitate to pass this
recommendation to your university library. This
book is
the primary
documentation for the 'nlme' package, which is part
of the
standard R
distribution. A subdirectory
~library\nlme\scripts of your R
installation includes files named ch01.R,
ch02.R, ...,
ch06.R,
ch08.R, containing the R scripts described in the
book. These R
script files make it much easier and more enjoyable
to study that
book, because they make it much easier to try the
commands
described
in the book, one line at a time, testing
Re: [R] Fwd: Variance Components in R
Hi, Iuri: How much RAM and how fast a microprocessor (and what version of Windows) do you have? You might still try it in R under Windows. The results might be comparable or dramatically better in R than in SPSS or SAS. hope this helps. Spencer Graves Iuri Gavronski wrote: 9500 records. It didn`t run in SPSS or SAS on Windows machines, so I am trying to convert the SPSS script to R to run in a RISC station at the university. On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote: Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data? -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski Sent: Thursday, August 17, 2006 11:08 AM To: Spencer Graves Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Variance Components in R Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ..., ch06.R, ch08.R, containing the R scripts described in the book. These R script files make it much easier and more enjoyable to study that book, because they make it much easier to try the commands described in the book, one line at a time, testing modifications to check you comprehension, etc. In addition to avoiding problems with typographical errors, it also automatically overcomes a few minor but substantive changes in the notation between S-Plus and R. Also, the MINQUE method has been obsolete for over 25 years. I recommend you use method = REML except for when you want to compare two nested models with different fixed effects; in that case, you should use method = ML, as explained in Pinheiro and Bates (2000). Hope this helps. Spencer Graves Iuri Gavronski wrote: Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = REML /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT
Re: [R] Fwd: Variance Components in R
We have tried on many machines, from my laptop to a dual core Intel processor with 1GB of RAM. On 8/17/06, Spencer Graves [EMAIL PROTECTED] wrote: Hi, Iuri: How much RAM and how fast a microprocessor (and what version of Windows) do you have? You might still try it in R under Windows. The results might be comparable or dramatically better in R than in SPSS or SAS. hope this helps. Spencer Graves Iuri Gavronski wrote: 9500 records. It didn`t run in SPSS or SAS on Windows machines, so I am trying to convert the SPSS script to R to run in a RISC station at the university. On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote: Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data? -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski Sent: Thursday, August 17, 2006 11:08 AM To: Spencer Graves Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Variance Components in R Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ..., ch06.R, ch08.R, containing the R scripts described in the book. These R script files make it much easier and more enjoyable to study that book, because they make it much easier to try the commands described in the book, one line at a time, testing modifications to check you comprehension, etc. In addition to avoiding problems with typographical errors, it also automatically overcomes a few minor but substantive changes in the notation between S-Plus and R. Also, the MINQUE method has been obsolete for over 25 years. I recommend you use method = REML except for when you want to compare two nested models with different fixed effects; in that case, you should use method = ML, as explained in Pinheiro and Bates (2000). Hope this helps. Spencer Graves Iuri Gavronski wrote: Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT /INTERCEPT = INCLUDE. VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = REML /DESIGN = CHAIN SECTOR RESP ASPECT ITEM SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM
Re: [R] Variance Components in R
I am trying to replicate Finn and Kayandé (1997) study on G-theory
application on Marketing. The idea is to have people evaluate some aspects
of service quality for chains on different economy sectors. Then, conduct a
G-study to identify the generalizability coefficient estimates for different
D-study designs.
I have persons rating 3 different items on 3 different aspects of service
quality on 3 chains on 3 sectors. It is normally assumed on G-studies that
the factors are random. So I have to specify a model to estimate the
variance components of CHAIN SECTOR RESP ASPECT ITEM, and the interaction of
SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM
RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT.
'*' in VARCOMP means a crossed design.
Evaluating only the two dimensions interactions (x*y) ran in few minutes
with the full database. Including three interactions (x*y*z) didn't complete
the execution at all. I have the data and script sent to a professor of the
department of Statistics on my university and he could not run it on either
SPSS or SAS (we don't have SAS licenses here at the business school, only
SPSS). Nobody here at the business school has any experience with R, so I
don't have anyone to ask for help.
Ì am not sure if I have answered you question, but feel free to ask it
again, and I will try to restate the problem.
Best regards,
Iuri
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
This will (should) be a piece of cake for lmer. But, I don't speak SPSS.
Can you write your model out as a linear model and give a brief description
of the data and your problem?
In addition to what Spencer noted as help below, you should also check out
the vignette in the mlmRev package. This will give you many examples.
vignette('MlmSoftRev')
--
*From:* [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] *On Behalf Of *Iuri
Gavronski
*Sent:* Thursday, August 17, 2006 11:16 AM
*To:* Doran, Harold
*Subject:* Re: [R] Variance Components in R
9500 records. It didn`t run in SPSS or SAS on Windows machines, so I am
trying to convert the SPSS script to R to run in a RISC station at the
university.
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
Iuri:
The lmer function is optimal for large data with crossed random effects.
How large are your data?
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski
Sent: Thursday, August 17, 2006 11:08 AM
To: Spencer Graves
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Variance Components in R
Thank you for your reply.
VARCOMP is available at SPSS advanced models, I'm not sure
for how long it exists... I only work with SPSS for the last
4 years...
My model only has crossed random effects, what perhaps would
drive me to lmer().
However, as I have unbalanced data (why it is normally called
'unbalanced design'? the data was not intended to be
unbalanced, only I could not get responses for all cells...),
I'm afraid that REML would take too much CPU, memory and time
to execute, and MINQUE would be faster and provide similar
variance estimates (please, correct me if I'm wrong on that point).
I only found MINQUE on the maanova package, but as my study
is very far from genetics, I'm not sure I can use this package.
Any comment would be appreciated.
Iuri
On 8/16/06, Spencer Graves [EMAIL PROTECTED] wrote:
I used SPSS over 25 years ago, but I don't recall
ever fitting a
variance components model with it. Are all your random
effects nested?
If they were, I would recommend you use 'lme' in the 'nlme' package.
However, if you have crossed random effects, I suggest you
try 'lmer'
associated with the 'lme4' package.
For 'lmer', documentation is available in Douglas
Bates. Fitting
linear mixed models in R. /R News/, 5(1):27-30, May 2005
(www.r-project.org - newsletter). I also recommend you try the
vignette available with the 'mlmRev' package (see, e.g.,
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html).
Excellent documentation for both 'lme' (and indirectly for
'lmer') is available in Pinheiro and Bates (2000)
Mixed-Effects Models
in S and S-Plus (Springer). I have personally recommended
this book
so many times on this listserve that I just now got 234 hits for
RSiteSearch(graves pinheiro). Please don't hesitate to pass this
recommendation to your university library. This book is
the primary
documentation for the 'nlme' package, which is part of the
standard R
distribution. A subdirectory ~library\nlme\scripts of your R
installation includes files named ch01.R, ch02.R, ...,
ch06.R,
ch08.R, containing the R scripts described in the book. These R
script files make it much easier and more enjoyable to study
Re: [R] nls convergence problem
Yours truly dieter.menne at menne-biomed.de writes: ... Recently, a colleague fitted gastric emptying curves using GraphPad, with 100% success, and nls failed for one third of these. When we checked GraphPads output more closely, some of the coefficients looked like 2.1 with a confidence interval in the range -27128 ... 314141. Nobody forces you to look at these, though, when using GraphPad. Since my comment has stirred a bit of an uproar, I should add that this is not the fault of GraphPad, but that most non-linear fitting programs, including those in the big SXXX, give the same results. Harvey Motulsky from Graphpad/Prism informed me that they were going to add special tests in the new versions. Their pdf-manual on nonlinear fitting is worth a look anyway if Bates/Watts is over your head. And if anyone want to see sample data: http://www.menne-biomed.de/gastempt/gastempt1.html I only wish nls were a little bit more polite in telling me what went wrong. I stand corrected: I only wish nls were less politically correct, but rather inform me WHY it faltered. Dieter __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Fwd: Variance Components in R
Burt Gunter just reminded me that the completion time could also be affected by the numbers of levels of each of the factors, especially random effects: With N records, any variance components / mixed model software using MLE or REML will have to invert repeatedly an N x N matrix for the covariance structure of the random effects and noise. If the software recognizes your design as having some simple structure, this can be quite fast; otherwise, it could be a Herculean task. In your case with N = 9500 records, just one copy of this covariance matrix could consume a substantial portion of 1GB RAM. I compute 8*9500*(9500-1)/2 = 361Mbytes. However, any software that recognizes special structure in your design may be able to do the required computations without ever constructing a matrix this large. I would say that it's still worth a try in R on your laptop or on the machine with 1GB RAM: 'lmer' might recognize special structure that neither of the other two do (and vice versa). Hope this helps. Spencer Graves Iuri Gavronski wrote: We have tried on many machines, from my laptop to a dual core Intel processor with 1GB of RAM. On 8/17/06, *Spencer Graves* [EMAIL PROTECTED] mailto:[EMAIL PROTECTED] wrote: Hi, Iuri: How much RAM and how fast a microprocessor (and what version of Windows) do you have? You might still try it in R under Windows. The results might be comparable or dramatically better in R than in SPSS or SAS. hope this helps. Spencer Graves Iuri Gavronski wrote: 9500 records. It didn`t run in SPSS or SAS on Windows machines, so I am trying to convert the SPSS script to R to run in a RISC station at the university. On 8/17/06, Doran, Harold [EMAIL PROTECTED] mailto:[EMAIL PROTECTED] wrote: Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data? -Original Message- From: [EMAIL PROTECTED] mailto:[EMAIL PROTECTED] [mailto: [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]] On Behalf Of Iuri Gavronski Sent: Thursday, August 17, 2006 11:08 AM To: Spencer Graves Cc: r-help@stat.math.ethz.ch mailto:r-help@stat.math.ethz.ch Subject: Re: [R] Variance Components in R Thank you for your reply. VARCOMP is available at SPSS advanced models, I'm not sure for how long it exists... I only work with SPSS for the last 4 years... My model only has crossed random effects, what perhaps would drive me to lmer(). However, as I have unbalanced data (why it is normally called 'unbalanced design'? the data was not intended to be unbalanced, only I could not get responses for all cells...), I'm afraid that REML would take too much CPU, memory and time to execute, and MINQUE would be faster and provide similar variance estimates (please, correct me if I'm wrong on that point). I only found MINQUE on the maanova package, but as my study is very far from genetics, I'm not sure I can use this package. Any comment would be appreciated. Iuri On 8/16/06, Spencer Graves [EMAIL PROTECTED] mailto:[EMAIL PROTECTED] wrote: I used SPSS over 25 years ago, but I don't recall ever fitting a variance components model with it. Are all your random effects nested? If they were, I would recommend you use 'lme' in the 'nlme' package. However, if you have crossed random effects, I suggest you try 'lmer' associated with the 'lme4' package. For 'lmer', documentation is available in Douglas Bates. Fitting linear mixed models in R. /R News/, 5(1):27-30, May 2005 (www.r-project.org http://www.r-project.org - newsletter). I also recommend you try the vignette available with the 'mlmRev' package (see, e.g., http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). Excellent documentation for both 'lme' (and indirectly for 'lmer') is available in Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). I have personally recommended this book so many times on this listserve that I just now got 234 hits for RSiteSearch(graves pinheiro). Please don't hesitate to pass this recommendation to your university library. This book is the primary documentation for the 'nlme' package, which is part of the standard R distribution. A subdirectory ~library\nlme\scripts of your R installation includes files named ch01.R, ch02.R, ...,
[R] rbind-ing vectors inside lists
Dear helpeRs,
suppose I have two lists as follows:
a = list(1:5,5:9)
b = lapply(a,*,2)
I would like to rbind-ing the two lists, that is I would like to use
something as rbind applied
component to component for the two list.
I have used the following solution:
fun.tile.wt = function(list1, list2)
{
for(i in 1:length(list1))
{
list1[[i]]=rbind(list1[[i]],list2[[i]])
}
list1
}
fun.tile.wt(a,b)
Is it possible to directly obtain the result using the apply family
(or something else)?
Any suggestions is appreciated.
Thanks in advance,
domenico vistocco
[[alternative HTML version deleted]]
Chiacchiera con i tuoi amici in tempo reale!
http://it.yahoo.com/mail_it/foot/*http://it.messenger.yahoo.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] rbind-ing vectors inside lists
Try:
mapply(rbind, a, b, SIMPLIFY = FALSE)
On 8/17/06, Domenico Vistocco [EMAIL PROTECTED] wrote:
Dear helpeRs,
suppose I have two lists as follows:
a = list(1:5,5:9)
b = lapply(a,*,2)
I would like to rbind-ing the two lists, that is I would like to use
something as rbind applied
component to component for the two list.
I have used the following solution:
fun.tile.wt = function(list1, list2)
{
for(i in 1:length(list1))
{
list1[[i]]=rbind(list1[[i]],list2[[i]])
}
list1
}
fun.tile.wt(a,b)
Is it possible to directly obtain the result using the apply family
(or something else)?
Any suggestions is appreciated.
Thanks in advance,
domenico vistocco
[[alternative HTML version deleted]]
Chiacchiera con i tuoi amici in tempo reale!
http://it.yahoo.com/mail_it/foot/*http://it.messenger.yahoo.com
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] unlink disables help?
I was hoping that someone could try to reproduce an error that I am
getting. The R Site Search keeps timing out on me, so apologies of this
has already come up.
I'm using
R.version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 3.1
year 2006
month 06
day01
svn rev38247
language R
version.string Version 2.3.1 (2006-06-01)
When I use unlink as below, the help system is disabled:
?print
testPath - tempdir()
print(testPath)
[1] C:\\WINDOWS\\TEMP\\Rtmpo5Wnqb
file.exists(testPath)
[1] TRUE
unlink(testPath, recursive = TRUE)
?print
Error in int.unzip(file.path(path, zipname), topic, tmpd) :
'destination' does not exist
I can produce the same error with Version 2.3.0 (2006-04-24) on Windows.
I haven't been able to reproduce this with directories that are created
using other means:
?print
testPath - c:\\tmp\\unlinkTest
dir.create(testPath)
file.exists(testPath)
[1] TRUE
unlink(testPath, recursive = TRUE)
?print
Thanks,
Max
--
LEGAL NOTICE\ Unless expressly stated otherwise, this messag...{{dropped}}
__
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] rbind-ing vectors inside lists
## initial example a = list(1:5, 5:9) b = lapply(a,*,2) library(abind) ## you may need to download abind from CRAN abind(data.frame(a), data.frame(b), along=.5) ## data.frames with column names a = data.frame(first=1:5, second=5:9) b = a^2 abind(a, b, along=.5, new.names=c(a,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] R Site Search directly from Firefox's address bar
Dear list, For all those interested who use Firefox as the main browser, here is a quick way to make R related searches: type about:config in the address bar search for keyword.url and modify it to http://finzi.psych.upenn.edu/cgi-bin/namazu.cgi?idxname=functionsidxname=docsidxname=Rhelp02aquery=; From now on, every keyword(s) you type in the address bar will take you directly to the first page of hits at http://finzi.psych.upenn.edu I found this very helpful. Best, Adrian -- Adrian Dusa Romanian Social Data Archive 1, Schitu Magureanu Bd 050025 Bucharest sector 5 Romania Tel./Fax: +40 21 3126618 \ +40 21 3120210 / int.101 __ 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] unlink disables help?
Kuhn, Max [EMAIL PROTECTED] writes: I was hoping that someone could try to reproduce an error that I am getting. The R Site Search keeps timing out on me, so apologies of this has already come up. I'm using R.version never mind When I use unlink as below, the help system is disabled: ?print testPath - tempdir() print(testPath) [1] C:\\WINDOWS\\TEMP\\Rtmpo5Wnqb file.exists(testPath) [1] TRUE unlink(testPath, recursive = TRUE) ?print Error in int.unzip(file.path(path, zipname), topic, tmpd) : 'destination' does not exist I can produce the same error with Version 2.3.0 (2006-04-24) on Windows. Read the documentation *carefully*: Value: For 'tempfile' For 'tempdir', the path of the per-session temporary directory. And there is only one, and it is in there that the help system keeps its stuff -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@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] day, month, year functions
On 8/17/06, Martin Maechler [EMAIL PROTECTED] wrote: Gregor == Gregor Gorjanc [EMAIL PROTECTED] on Fri, 11 Aug 2006 00:27:27 + (UTC) writes: Gregor Gabor Grothendieck ggrothendieck at gmail.com writes: Here are three ways: xx - as.Date(2006-01-05) # 1. use as.POSIXlt as.POSIXlt(xx)$mday as.POSIXlt(xx)$mon + 1 as.POSIXlt(xx)$year + 1900 # 2. use format as.numeric(format(xx, %d)) as.numeric(format(xx, %m)) as.numeric(format(xx, %Y)) # 3. use month.day.year in chron package library(chron) month.day.year(unclass(xx))$day month.day.year(unclass(xx))$month month.day.year(unclass(xx))$year Gregor Hi, Gregor it would really be great if there would be Gregor sec(), min(), hour() day(), month(), year() Gregor generic functions that would work on all date classes. Where Gregor applicable of course. I imagine that argument to get out integer Gregor or character would alse be nice. I disagree pretty strongly: - We definitely don't want min() to return minutes instead of minimum ! - Why pollute the namespace with 6 (well, actualy 5!) new function names, when as.POSIXlt() *REALLY* is there exactly for this purpose ??? I rather think the authors of each of the other old-fashioned date classes should provide as.POSIXlt() methods for their classes. Then, we'd have uniform interfaces, following's Gabor's # 1. above. Martin Maechler, ETH Zurich There are two problems: 1. as.POSIXlt is not generic. (This problem may not be too important given that as.POSIXlt does handle Date and chron dates classes already but in terms of handling all potential classes its a limitation.) 2. in the case of as.POSIXlt converting chron dates objects to POSIXlt there is a time zone consideration, as shown below, where today, August 17th in the Eastern Daylight Time zone, is displayed as August 16th using as.POSIXlt unless we use tz = GMT library(chron) # today is August 17th. Sys.Date() [1] 2006-08-17 chron(unclass(Sys.Date())) [1] 08/17/06 Sys.time() [1] 2006-08-17 14:28:19 Eastern Daylight Time as.POSIXlt(Sys.Date()) [1] 2006-08-17 as.POSIXlt(chron(unclass(Sys.Date( [1] 2006-08-16 20:00:00 Eastern Daylight Time as.POSIXlt(chron(unclass(Sys.Date())), tz = GMT) [1] 2006-08-17 GMT R.version.string # Windows XP [1] Version 2.3.1 Patched (2006-06-04 r38279) __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] R Site Search directly from Firefox's address bar
Adrian Dusa [EMAIL PROTECTED] writes: Dear list, For all those interested who use Firefox as the main browser, here is a quick way to make R related searches: type about:config in the address bar search for keyword.url and modify it to http://finzi.psych.upenn.edu/cgi-bin/namazu.cgi?idxname=functionsidxname=docsidxname=Rhelp02aquery=; From now on, every keyword(s) you type in the address bar will take you directly to the first page of hits at http://finzi.psych.upenn.edu I found this very helpful. Breaks the feature that you get to www.r-project.org just by typing r, though... -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Boxplot Help: Re-ordering the x-axis
I am having a problem using boxlpot with my data. I have my data arranged in a data table, and two of my columns are mass and month. I am trying to plot the mass of my study animals by month, thus I would like to have it in the order of January to December. The problem is that R orders each month in alphabetical order, and gives each month an integer value corresponding to this (i.e. April is integer=1, August=2, September=12). I have tried many different ways to solve this but nothing is working. If anyone knows how to order the x-axis in boxplot, or alternatively, re-assign integer values to each month that would be very helpful. Thank you in advance! Pamela Allen, MSc Candidate University of British Columbia Marine Mammal Research Unit, Fisheries Centre Vancouver, B.C. V6T 1Z4 [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] R Site Search directly from Firefox's address bar
On Thursday 17 August 2006 21:41, Peter Dalgaard wrote: [...] Breaks the feature that you get to www.r-project.org just by typing r, though... Oh, this is very simple to fix. I created a bookmark named R with the above location and assigned it a keyword r. Now, everytime I type r in the address bar it takes me to www.r-project.org :) -- Adrian Dusa Romanian Social Data Archive 1, Schitu Magureanu Bd 050025 Bucharest sector 5 Romania Tel./Fax: +40 21 3126618 \ +40 21 3120210 / int.101 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Boxplot Help: Re-ordering the x-axis
On Thu, 2006-08-17 at 11:46 -0700, Pamela Allen wrote: I am having a problem using boxlpot with my data. I have my data arranged in a data table, and two of my columns are mass and month. I am trying to plot the mass of my study animals by month, thus I would like to have it in the order of January to December. The problem is that R orders each month in alphabetical order, and gives each month an integer value corresponding to this (i.e. April is integer=1, August=2, September=12). I have tried many different ways to solve this but nothing is working. If anyone knows how to order the x-axis in boxplot, or alternatively, re-assign integer values to each month that would be very helpful. Thank you in advance! Note the following in the Details section of ?boxplot: If multiple groups are supplied either as multiple arguments or via a formula, parallel boxplots will be plotted, in the order of the arguments or the order of the levels of the factor (see factor). If you are using a formula approach, then something like the following: month - factor(month, levels = c(January, February, ..., November, December) boxplot(mass ~ month) See ?factor For future reference, using: RSiteSearch(boxplot order) will search the r-help archive using the indicated key words, where you will see that this has been covered previously. 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] Boxplot Help: Re-ordering the x-axis
month.name class(month.name) character tmp - data.frame(m=rep(month.name, 2), y=rnorm(24)) bwplot(y ~ m, data=tmp) tmp - data.frame(m=ordered(rep(month.name, 2), levels=month.name), y=rnorm(24)) bwplot(y ~ m, data=tmp) __ 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] problem with cut(as.Date(2006-08-14), week)
When I run cut.Date or cut.POSIXt with argument breaks = weeks, the function gives the first day of that week, unless the date is the first day of the week, in which case it gives an error message as in: cut(as.Date(2006-08-16), week) [1] 2006-08-14 Levels: 2006-08-14 cut(as.Date(2006-08-14), week) Error in 1:(1 + max(which(breaks maxx))) : result would be too long a vector In addition: Warning message: no non-missing arguments to max; returning -Inf sessionInfo() Version 2.3.1 (2006-06-01) i386-pc-mingw32 attached base packages: [1] methods stats graphics grDevices utils datasets [7] base Sys.getlocale() [1] LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 Bug or feature? Mikkel __ 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] NLME: Limitations of using identify to interact with scatterplots?
Hi Take a look at panel.identify() (in the 'lattice' package). I'm not sure if it will help you because I cannot run your example code. Paul Douglas Bates wrote: Most plotting functions in the nlme package use lattice graphics functions based on the grid package. Identify will not work with lattice graphics. I'm not sure if there is a replacement. On 8/17/06, Greg Distiller [EMAIL PROTECTED] wrote: I have a quick question regarding the use of identify to interact with points on a scatterplot. My question is essentially: can identify be used when one is plotting model objects to generate diagnostic plots? Specifically I am using NLME. For example, I am plotting the fitted values on the x axis vs a variable called log2game with the following code: plot(D2C29.nlme, log2game ~ fitted(.), abline=c(0,1)) and then I have tried to use identify as follows: identify(D2C29.nlme$fitted[,2],Data2$log2game,row.names(Data2)) (if I leave out the [,2] on the fitted attributes then I am told that x and y are not the same length and it appears that this is due to the fact that the fitted attribute has 2 columns.) but I get an error message that plot.new has not been called yet. I am not sure if this is because I am doing something wrong or if identify simply cannot be used in this context. Many thanks Greg __ 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. -- Dr Paul Murrell Department of Statistics The University of Auckland Private Bag 92019 Auckland New Zealand 64 9 3737599 x85392 [EMAIL PROTECTED] http://www.stat.auckland.ac.nz/~paul/ __ 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] Rgraphviz fails to load
Dear r-helpers, Can anyone suggest a remedy to the following failure of Rgraphviz to load? library(Rgraphviz) Loading required package: graph Loading required package: Ruuid Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library '/Library/Frameworks/R.framework/ Resources/library/Rgraphviz/libs/ppc/Rgraphviz.so': dlopen(/Library/Frameworks/R.framework/Resources/library/Rgraphviz/ libs/ppc/Rgraphviz.so, 6): Library not loaded: /usr/local/lib/libpng. 3.dylib Referenced from: /usr/local/lib/graphviz/libgvc.2.dylib Reason: image not found Error: .onLoad failed in 'loadNamespace' for 'Rgraphviz' Error: package/namespace load failed for 'Rgraphviz' Version 2.3.1 (2006-06-01) powerpc-apple-darwin8.6.0 attached base packages: [1] utils methods stats graphics grDevices datasets base other attached packages: graph RuuidJGR JavaGD rJava MASS lattice 1.10.6 1.10.01.4-40.3-40.4-5 7.2-27.1 0.13-10 _ 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] Simulate p-value in lme4
Dear list,
This is more of a stats question than an R question per se. First, I
realize there has been a lot of discussion about the problems with
estimating P-values from F-ratios for mixed-effects models in lme4.
Using mcmcsamp() seems like a great alternative for evaluating the
significance of individual coefficients, but not for groups of
coefficients as might occur in an experimental design with 3 treatment
levels. I'm wondering if the simulation approach I use below to estimate
the P-value for a 3-level factor is appropriate, or if there are any
suggestions on how else to approach this problem. The model and data in
the example are from section 10.4 of MASS.
Thanks!
Manuel
# Load req. package (see functions to generate data at end of script)
library(lme4)
library(MASS)
# Full and reduced models - pred is a factor with 3 levels
result.full - lmer(y~pred+(1|subject), data=epil3, family=poisson)
result.base - lmer(y~1+(1|subject), data=epil3, family=poisson)
# Naive P-value from LR for significance of pred factor
anova(result.base,result.full)$Pr(Chisq)[[2]] # P-value
(test.stat - anova(result.base,result.full)$Chisq[[2]]) # Chisq-stat
# P-value from simulation. Note that in the simulation, I use the
# estimated random effects for each subject rather than generating a new
# distribution of means. I'm not sure if this is appropriate or not ...
intercept - fixef(result.base)
rand.effs - ranef(result.base)[[1]]
mu - exp(rep(intercept+rand.effs[[1]],2))
p.value - function(iter, stat) {
chi.stat - vector()
for(i in 1:iter) {
resp - rpois(length(mu), mu) # simulate values
sim.data - data.frame(y=resp,subject=epil3$subject,pred=epil3$pred)
result.f - lmer(y~pred+(1|subject), data=sim.data,
family=poisson)
result.b - lmer(y~1+(1|subject), data=sim.data, family=poisson)
chi.stat[i] - anova(result.b,result.f)$Chisq[[2]]
}
val - sum(unlist(lapply(chi.stat, function(x) if(xstat) 1 else
0)))/iter
hist(chi.stat)
return(val)
}
p.value(10,test.stat) # Increase to =1000 to get a reasonable P-value!
# Script to generate data, from section 10.4 of MASS
epil2 - epil[epil$period == 1, ]
epil2[period] - rep(0, 59); epil2[y] - epil2[base]
epil[time] - 1; epil2[time] - 4
epil2 - rbind(epil, epil2)
epil2$pred - unclass(epil2$trt) * (epil2$period 0)
epil2$subject - factor(epil2$subject)
epil3 - aggregate(epil2, list(epil2$subject, epil2$period 0),
function(x) if(is.numeric(x)) sum(x) else x[1])
epil3$pred - factor(epil3$pred, labels = c(base, placebo, drug))
__
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] Variance Components in R
Iuri:
Here is an example of how a model would be specified using lmer using a couple
of your factors:
fm - lmer(response.variable ~ chain*sector*resp
+(chain*sector*resp|GroupingID), data)
This will give you a main effect for each factor and all possible interactions.
However, do you have a grouping variable? I wonder if aov might be the better
tool for your G-study?
As a side note, I don't see that you have a factor for persons. Isn't this also
a variance component of interest for your study?
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Iuri
Gavronski
Sent: Thursday, August 17, 2006 1:26 PM
To: Doran, Harold
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Variance Components in R
I am trying to replicate Finn and Kayandé (1997) study on G-theory
application on Marketing. The idea is to have people evaluate some aspects of
service quality for chains on different economy sectors. Then, conduct a
G-study to identify the generalizability coefficient estimates for different
D-study designs.
I have persons rating 3 different items on 3 different aspects of
service quality on 3 chains on 3 sectors. It is normally assumed on G-studies
that the factors are random. So I have to specify a model to estimate the
variance components of CHAIN SECTOR RESP ASPECT ITEM, and the interaction of
SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP CHAIN*ASPECT CHAIN*ITEM
RESP*ASPECT RESP*ITEM SECTOR*RESP*ASPECT SECTOR*RESP*ITEM CHAIN*RESP*ASPECT.
'*' in VARCOMP means a crossed design.
Evaluating only the two dimensions interactions (x*y) ran in few
minutes with the full database. Including three interactions (x*y*z) didn't
complete the execution at all. I have the data and script sent to a professor
of the department of Statistics on my university and he could not run it on
either SPSS or SAS (we don't have SAS licenses here at the business school,
only SPSS). Nobody here at the business school has any experience with R, so I
don't have anyone to ask for help.
Ì am not sure if I have answered you question, but feel free to ask it
again, and I will try to restate the problem.
Best regards,
Iuri
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
This will (should) be a piece of cake for lmer. But, I don't
speak SPSS. Can you write your model out as a linear model and give a brief
description of the data and your problem?
In addition to what Spencer noted as help below, you should
also check out the vignette in the mlmRev package. This will give you many
examples.
vignette('MlmSoftRev')
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Iuri Gavronski
Sent: Thursday, August 17, 2006 11:16 AM
To: Doran, Harold
Subject: Re: [R] Variance Components in R
9500 records. It didn`t run in SPSS or SAS on Windows machines,
so I am trying to convert the SPSS script to R to run in a RISC station at the
university.
On 8/17/06, Doran, Harold [EMAIL PROTECTED] wrote:
Iuri:
The lmer function is optimal for large data with
crossed random effects.
How large are your data?
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski
Sent: Thursday, August 17, 2006 11:08 AM
To: Spencer Graves
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Variance Components in R
Thank you for your reply.
VARCOMP is available at SPSS advanced models, I'm not
sure
for how long it exists... I only work with SPSS for
the last
4 years...
My model only has crossed random effects, what
perhaps would
drive me to lmer().
However, as I have unbalanced data (why it is
normally called
'unbalanced design'? the data was not intended to be
unbalanced, only I could not get responses for all
cells...),
I'm afraid that REML would take too much CPU, memory
and time
to
[R] getting sapply to skip columns with non-numeric data?
getting s-apply to skip columns with non-numeric data? I have a dataframe x of w columns. Some columns are numeric, some are not. I wish to create a function to calculate the mean and standard deviation of each numeric column, and then bind the column mean and standard deviation to the bottom of the dataframe. e.g. tempmean - apply(data.frame(x), 2, mean, na.rm = T) xnew - rbind(x,tempmean) I am running into one small problem what is the best way to have sapply skip the non-numeric data and return NAs? __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] R Site Search directly from Firefox's address bar
Adrian Dusa dusa.adrian at gmail.com writes: On Thursday 17 August 2006 21:41, Peter Dalgaard wrote: [...] Breaks the feature that you get to www.r-project.org just by typing r, though... Oh, this is very simple to fix. I created a bookmark named R with the above location and assigned it a keyword r. Now, everytime I type r in the address bar it takes me to www.r-project.org :) Or add a '%s' to your bookmark definition: http://finzi.psych.upenn.edu/cgi-bin/namazu.cgi?idxname=functionsidxname=docsidxname=Rhelp02aquery=%s; and assign it the keyword 'rsite' then 'rsite search terms' will do the search :-) __ 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] getting sapply to skip columns with non-numeric data?
Use the first few rows of iris as test data and try this where isnum is 1 for each numeric column and NA for others. irish - head(iris) isnum - ifelse(sapply(iris, class) == numeric, 1, NA) iris.data - data.matrix(iris) rbind(iris, colMeans(iris.data) * isnum, sd(iris.data) * isnum) On 8/17/06, r user [EMAIL PROTECTED] wrote: getting s-apply to skip columns with non-numeric data? I have a dataframe x of w columns. Some columns are numeric, some are not. I wish to create a function to calculate the mean and standard deviation of each numeric column, and then bind the column mean and standard deviation to the bottom of the dataframe. e.g. tempmean - apply(data.frame(x), 2, mean, na.rm = T) xnew - rbind(x,tempmean) I am running into one small problem…what is the best way to have sapply skip the non-numeric data and return NA's? __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] getting sapply to skip columns with non-numeric data?
There's something that either you have not thought of or neglected to tell us: If you have k variables in the data frame, you will need a data frame of k variables and one row to be able to rbind() to the bottom of the original one. What are you going to put in place for non-numeric variables? Perhaps this might help: R dat - data.frame(f=factor(1:3), x=3:5, y=6:4) R rbind(dat, as.data.frame(lapply(dat, function(x) if (!is.numeric(x)) NA else mean(x f x y 1 1 3 6 2 2 4 5 3 3 5 4 11 NA 4 5 Andy From: r user getting s-apply to skip columns with non-numeric data? I have a dataframe x of w columns. Some columns are numeric, some are not. I wish to create a function to calculate the mean and standard deviation of each numeric column, and then bind the column mean and standard deviation to the bottom of the dataframe. e.g. tempmean - apply(data.frame(x), 2, mean, na.rm = T) xnew - rbind(x,tempmean) I am running into one small problem...what is the best way to have sapply skip the non-numeric data and return NA's? __ 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] DSC 2007
Hi This is a second call for abstracts. Please forward and circulate to other interested parties. [apologies for any cross-posting] DSC 2007, a conference on systems and environments for statistical computing, will take place in Auckland, New Zealand on February 15 16, 2007. We invite abstracts on the development of software systems and computing environments for interactive statistics. The workshop will focus on, but is not limited to, open source statistical computing. The deadline for submitting abstracts is 2006-10-15 (October 15th). Please visit the conference web page at http://www.stat.auckland.ac.nz/dsc-2007/ and send abstracts (one page) to [EMAIL PROTECTED] Paul (on behalf of the Organising Committee) -- Dr Paul Murrell Department of Statistics The University of Auckland Private Bag 92019 Auckland New Zealand 64 9 3737599 x85392 [EMAIL PROTECTED] http://www.stat.auckland.ac.nz/~paul/ ___ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-announce __ 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] Font-path error when starting X11 device in Gentoo
Dear R listers, If I try to start the X11 device in Gentoo, I get the following complaint from R: --- X11() Error in X11() : could not find any X11 fonts Check that the Font Path is correct. --- xset -q produces the following output: --- Keyboard Control: auto repeat: onkey click percent: 0LED mask: 0002 auto repeat delay: 500repeat rate: 30 auto repeating keys: 00ffdbbf fadfffdfffdfe5ef bell percent: 50bell pitch: 400bell duration: 100 Pointer Control: acceleration: 2/1threshold: 4 Screen Saver: prefer blanking: yesallow exposures: yes timeout: 0cycle: 0 Colors: default colormap: 0x20BlackPixel: 0WhitePixel: 16777215 Font Path: /usr/share/fonts/misc/,/usr/share/fonts/TTF/,/usr/share/fonts/Type1/,/usr/share/fonts/75dpi/,/usr/share/fonts/100dpi/ Bug Mode: compatibility mode is disabled DPMS (Energy Star): Standby: 3600Suspend: 3600Off: 7200 DPMS is Enabled Monitor is On File paths: Config file: /etc/X11/xorg.conf Modules path: /usr/lib/xorg/modules Log file: /var/log/Xorg.0.log --- Furthermore, no other graphics applications are complaining about not finding fonts. By the way, this happens both with the Gentoo ebuilds (2.2.1 and 2.3.1) of R, as well as with the source tarball from the R website, compiled manually (with X support, of course). Any suggestions? Thanks, Toby __ 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] Fitting Truncated Lognormal to a truncated data set (was: fitting truncated normal distribution)
Dear List,
I am trying to fit Truncated Lognormal to a data set that is
'truncated' from above a certain value, say, 0.01. Below is what I
was able to come up with. I would appreciate it if you could review
and make any necessary changes.
# This is modified off the code for 'dtnorm' of library(msm).
dtlnorm - function (n, mean = 0, sd = 1, lower = -Inf, upper = Inf)
{
ret - numeric()
if (length(n) 1)
n - length(n)
while (length(ret) n) {
y - rlnorm(n - length(ret), mean, sd)
y - y[y = lower y = upper]
ret - c(ret, y)
}
stopifnot(length(ret) == n)
ret
}
# This is modified off the code for 'rtnorm' of the library(msm).
rtlnorm - function (n, mean = 0, sd = 1, lower = -Inf, upper = Inf)
{
ret - numeric()
if (length(n) 1)
n - length(n)
while (length(ret) n) {
y - rlnorm(n - length(ret), mean, sd)
y - y[y = lower y = upper]
ret - c(ret, y)
}
stopifnot(length(ret) == n)
ret
}
x - rtlnorm(100, mean=-11.64857, sd = 3.422795, 0.01)
fitting truncated normal distribution on 8/16/2006.
dtlnorm0 - function(x, mean = 0, sd = 1)
{
dtlnorm(x, mean, sd, 0.01, Inf)
}
fitdistr(x, dtlnorm0, start = list(mean = -11, sd = 1))
Thank you.
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major2
minor2.1
year 2005
month12
day 20
svn rev 36812
language R
__
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] NLME: Limitations of using identify to interact with scatterplots?
Many useful diagnostic plots can be recreated in the usual plot() framework, with only a little coding effort. In this case, I would imagine that plot(dframe$log2game, fitted(D2C29.nlme)) abline(0,1) should get pretty close, if the name of the dataframe containing the variable is 'dframe'. Andrew On Thu, Aug 17, 2006 at 08:55:41AM -0500, Douglas Bates wrote: Most plotting functions in the nlme package use lattice graphics functions based on the grid package. Identify will not work with lattice graphics. I'm not sure if there is a replacement. On 8/17/06, Greg Distiller [EMAIL PROTECTED] wrote: I have a quick question regarding the use of identify to interact with points on a scatterplot. My question is essentially: can identify be used when one is plotting model objects to generate diagnostic plots? Specifically I am using NLME. For example, I am plotting the fitted values on the x axis vs a variable called log2game with the following code: plot(D2C29.nlme, log2game ~ fitted(.), abline=c(0,1)) and then I have tried to use identify as follows: identify(D2C29.nlme$fitted[,2],Data2$log2game,row.names(Data2)) (if I leave out the [,2] on the fitted attributes then I am told that x and y are not the same length and it appears that this is due to the fact that the fitted attribute has 2 columns.) but I get an error message that plot.new has not been called yet. I am not sure if this is because I am doing something wrong or if identify simply cannot be used in this context. Many thanks Greg __ 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. -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 Email: [EMAIL PROTECTED] http://www.ms.unimelb.edu.au __ 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] Lattice package par.settings/trellis.par.settings questions
Hi All, I'm trying to modify some of the default graphic parameters in a conditional histogram. While I was able to change the default grey background to white, I couldn't change the axis.font or the xlab font. I used the following code: /histogram(~V751|V013+V025, finalbase, xlab=Heard of HIV/AIDS (No/Yes), col=c(cyan,magenta), par.settings=list(background=white)) /The arguments for example like /axis.font=2/, or /cex=2/ are not working in the /par.settings(). /I also tried to read the manual of /trellis.par.settings()/ but didn't understand how to use it and where exactly to put it. Any help with this will be appreciated. Thanks, Debarchana. -- Debarchana Ghosh Research Assistant Department of Geography University of Minnesota PH: 8143607580 email to: [EMAIL PROTECTED] www.tc.umn.edu/~ghos0033 __ 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] Lattice package par.settings/trellis.par.settings questions
The parameter names are axis.text$font and axis.text$cex . Try issuing the command: trellis.par.get() to get a complete list. Here is an example: histogram(1:10, par.settings = list(axis.text = list(font = 2, cex = 0.5))) On 8/17/06, Debarchana Ghosh [EMAIL PROTECTED] wrote: Hi All, I'm trying to modify some of the default graphic parameters in a conditional histogram. While I was able to change the default grey background to white, I couldn't change the axis.font or the xlab font. I used the following code: /histogram(~V751|V013+V025, finalbase, xlab=Heard of HIV/AIDS (No/Yes), col=c(cyan,magenta), par.settings=list(background=white)) /The arguments for example like /axis.font=2/, or /cex=2/ are not working in the /par.settings(). /I also tried to read the manual of /trellis.par.settings()/ but didn't understand how to use it and where exactly to put it. Any help with this will be appreciated. Thanks, Debarchana. -- Debarchana Ghosh Research Assistant Department of Geography University of Minnesota PH: 8143607580 email to: [EMAIL PROTECTED] www.tc.umn.edu/~ghos0033 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lattice package par.settings/trellis.par.settings questions
Please read about lattice.par.settings, and not trellis.par.settings. Trellis is in S/S-plus. Anupam. __ 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.
