Re: [R] TeX distribution on Windows
On Mon, Sep 05, 2005 at 06:55:26PM -0400, Duncan Murdoch wrote: Göran Broström wrote: I'm looking for a Windows distribution of TeX that works with R, after a few years' absence from Windows. On Duncan Murdoch's Rtools page fptex is still recommended, but it turns out that fptex is defunct as of May 2005, see http://www.metz.supelec.fr/~popineau/xemtex-7.html So, what is suggested? TUG (tug.org) recommends something called proTeXt, which is said to be based on MiKTeX, for Windows users. Since MikTeX could be used with R, that sounds like a good alternative. I use MikTeX, with one or another of the workarounds listed on my page. I've never tried proTeXt; I did a little googling, but I still don't see the point of it exactly. It's just MiKTeX with a few extras, like WinEdt, ghostscript, etc. As far as I understand, MikTeX itself is untouched. fptex is still available in various repositories, and is likely to keep working for quite a long time: R doesn't demand the latest and greatest innovations from TeX/eTeX. Right. But maybe you should change the broken link to www.fptex.org. Göran __ 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
Re: [R] The Perils of PowerPoint
For some reason (probably that our organisation has blocked the site) I could not see the original articles that prompted the post. I however immediately assumed that this was precipitated by Tufte and his comments about PowerPoint (I recall seeing a good example of PowerPoint on his site) http://www.edwardtufte.com/tufte/powerpoint When this first came up I recall some dispute about the comments www.sociablemedia.com/articles_dispute.htm and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. Other links that are lying on my computer are In defense of PowerPoint http://www.jnd.org/dn.mss/in_defense_of_powerp.html and Does PowerPoint make you stupid? at http://www.presentations.com/presentations/delivery/article_display.jsp?vnu_content_id=1000482464 Tom -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Tim Churches Sent: Saturday, 3 September 2005 10:08 AM To: [EMAIL PROTECTED] Cc: Achim Zeileis; r-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint (Ted Harding) wrote: By the way, the Washington Post/Minneapolis Star Tribune article is somewhat reminiscent of a short (15 min) broadcast on BBC Radio 4 back on October 18 2004 15:45-16:00 called Microsoft Powerpoint and the Decline of Civilisation which explores similar themes and also frequently quotes Tufte. Unfortunately it lapsed for ever from Listen Again after the statutory week, so I can't point you to a replay. (However, I have carefully preserved the cassette recording I made). Try http://sooper.org/misc/powerpoint.mp3 (copyright law notwithstanding...) Tim 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 __ 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
Re: [R] model selection vs. H0 based testing
Hello, I wish to thank Douglas Bates very much for clarification and pointing me to the MCMC simulation method to get p values even for cases where Wald tests are inappropriate. One question however remains when publishing statistical results: does it help readers if we combine both, - AIC based model selection *and* - null hypothesis based tests statistics or should we focus on model selection only and try to reduce the amount of tables provided? Apologies if this is question is too much off-topic, so you may decide to answer off-list. I will give a short summary at the end. Thomas P. An article explaining the background: Johnson, J. Omland, K.S., Model Selection in Ecology and Evolution. Trends in Ecology and Evolution, 2004, 19 , 101-108 __ 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
Re: [R] SpatStat Kest - Error Message help
AB == Adrian Baddeley [EMAIL PROTECTED] on Mon, 5 Sep 2005 10:10:31 +0800 writes: AB On Thu, 1 Sep 2005, DrakeGis wrote: Hi I'm working with the function Kest in the package SpatStat (under LINUX with R 2.1.0). In order to evaluate the statistical significance of my point pattern I'm doing 999 Montecarlo replications. The script that use the Kest function runs OK for most of the different point patterns that I have but for a particular point pattern, which have only 17 points, it runs until the 34th iteration and then I receive this message: Error in [-(`*tmp*`, index, value = NULL) : incompatible types (1000) in subassignment type fix Execution halted Do you have any idea about what could be the cause of this ? Thanks in advance. AB This is not an error message from 'spatstat' itself. AB The message has been generated by the function [- AB which is called when you assign values to a subset of a dataset AB (in a command like x[z] - v). The message appears to say that the AB replacement value v is not of the same type as the original vector x. yes. And please get into the habit of saying traceback() after such an error. This would have quickly revealed if the error came from R function called from a function from 'spatstat' or not. Also, maybe more people should learn about `basic debugging', by using something like options(error = recover) or options(error = dump.frames) ## needs a later call to debugger() before running the script that produces the error. The end of the examples ?options show an example to use when running an R script. AB You say that you are running a script that uses the Kest function. AB The error is probably inside that script. If you send the script to us AB we can probably spot the problem for you. AB As Rolf mentioned in his email, spatstat provides a AB command envelope to compute simulation envelopes. This AB might be sufficient for your needs. AB regards AB Adrian Baddeley Regards, Martin Maechler __ 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
[R] r: chinese installation of r
can any one help: A friends query: My pc is using the chinese version windows xp, so when I installed R Chinese was automatically selected as the default language.How can I change it? It brings a lot of trouble since some of the output is in chinese too.__ 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
[R] : r: chinese installation of r
In the selection components step of installation,uncheck the message translations.Then it will be OK! - 原邮件 - 从: Clark Allan [EMAIL PROTECTED] 日期: 星期二, 九月 6日, 2005 下午5:55 主题: [R] r: chinese installation of r can any one help: A friends query: My pc is using the chinese version windows xp, so when I installed R Chinese was automatically selected as the default language.How can I change it? It brings a lot of trouble since some of the output is in chinese too. __ 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 __ 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
Re: [R] r: chinese installation of r
Clark Allan schrieb: can any one help: A friends query: My pc is using the chinese version windows xp, so when I installed R Chinese was automatically selected as the default language.How can I change it? It brings a lot of trouble since some of the output is in chinese too. The R admin manual http://cran.r-project.org/doc/manuals/R-admin.html says: The preferred language for messages is by default taken from the locale. This can be overridden first by the setting of the environment variable LANGUAGE and then by the environment variables LC_ALL, LC_MESSAGES and LANG. (The last three are normally used to set the locale and so should not be needed, but the first is only used to select the language for messages.) The code tries hard to map locale names to languages, even on Windows. Note that you should not expect to be able to change the language once R is running. If your system runs on Windows, define a variable LANGUAGE in the systems settings (environment) and set it to EN. Hope it helps Thomas Petzoldt __ 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
[R] R: optim
hi all
i dont understand the error message that is produced by the optim
function. can anybody help???
ie:
[[1]]$message
[1] CONVERGENCE: REL_REDUCTION_OF_F = FACTR*EPSMCH
can anyone help?
###
SK.FIT(XDATA=a,XDATAname=a,PHI1=1,v=5,vlo=2,vhi=300,phi2lo=.01)
[[1]]
[[1]]$par
[1] -0.01377906 0.83859445 0.34675230 300.
[[1]]$value
[1] 90.59185
[[1]]$counts
function gradient
53 53
[[1]]$convergence
[1] 0
[[1]]$message
[1] CONVERGENCE: REL_REDUCTION_OF_F = FACTR*EPSMCH
#
i ghave included the function used in the optim call:
SKEWMLE=function(l,DATA=XDATA,...)
{
#alpha = l[1]
#beta = l[2]
#phi2 = l[3]
#v= l[4]
phi1=PHI1
DATA-as.matrix(DATA)
fnew-function(x,y,l,...)
{
#when we do not estimate phi1
t1=(1+((y-l[1]-l[2]*x)^2)/(l[4]*l[3]^2))^(-0.5*(1+l[4]))
t2=(1+(x^2)/l[4])^(-0.5*(1+l[4]))
t3=2*((gamma(0.5*(1+l[4]))/(gamma(0.5*l[4])*sqrt(l[4]*pi)))^2)/l[3]
t1*t2*t3
}
a-double(length(DATA))
y=DATA
a=apply(y,1,function(q)
log(integrate(fnew,lower=0,upper=Inf,y=q,l=l)$value))
-sum(a)
}__
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
Re: [R] Doubt about nested aov output
Hi Spencer, Em Dom 04 Set 2005 20:31, Spencer Graves escreveu: Others may know the answer to your question, but I don't. However, since I have not seen a reply, I will offer a few comments: 1. What version of R are you using? I just tried superficially similar things with the examples in ?aov in R 2.1.1 patched and consistently got F and p values. I'm using the R version 2.1.1 on Linux Debian Version 2.1.1 (2005-06-20), ISBN 3-900051-07-0 2. My preference for this kind of thing is to use lme in library(nlme) or lmer in library(lme4). Also, I highly recommend Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). Yes, this is my preference too, but I need aov for classes. 3. If still want to use aov and are getting this problem in R 2.1.1, could you please provide this list with a small, self contained example that displays the symptoms that concern you? And PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html;. It might increase the speed and utility of replies. spencer graves I send the complete example. This is a example from the Crwaley's book (Statistical Computing: An introdution to data analysis using S-Plus. This is a classical experiment to show pseudoreplication, from Sokal and Rohlf (1995). In this experiments, It have 3 treatmens applied to 6 rats, for each rat it make 3 liver preparation and for each liver it make 2 readings of glycogen. This generated 6 pseudoreplication per rat. I'm interested on the effect os treatment on the glycogen readings. Look the R analyses: Glycogen - c(131,130,131,125,136,142,150,148,140,143,160,150,157,145,154,142,147,153,151,155,147,147,162,152,134,125,138,138,135,136,138,140,139,138,134,127) Glycogen [1] 131 130 131 125 136 142 150 148 140 143 160 150 157 145 154 142 147 153 151 [20] 155 147 147 162 152 134 125 138 138 135 136 138 140 139 138 134 127 Treatment - factor(rep(c(1,2,3),c(12,12,12))) Treatment [1] 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 Levels: 1 2 3 Rat - factor(rep(rep(c(1,2),c(6,6)),3)) Rat [1] 1 1 1 1 1 1 2 2 2 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 Levels: 1 2 Liver - factor(rep(rep(c(1,2,3),c(2,2,2)),6)) Liver [1] 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 Levels: 1 2 3 ### Model made identical to the book model - aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver)) summary(model) Error: Treatment Df Sum Sq Mean Sq Treatment 2 1557.56 778.78 Error: Treatment:Rat Df Sum Sq Mean Sq Treatment:Rat 3 797.67 265.89 Error: Treatment:Rat:Liver Df Sum Sq Mean Sq Treatment:Rat:Liver 12 594.049.5 Error: Within Df Sum Sq Mean Sq F value Pr(F) Residuals 18 381.00 21.17 ### Model made by myself, I'm interested only in Treatment effects model - aov(Glycogen~Treatment+Error(Treatment/Rat/Liver)) summary(model) Error: Treatment Df Sum Sq Mean Sq Treatment 2 1557.56 778.78 Error: Treatment:Rat Df Sum Sq Mean Sq F value Pr(F) Residuals 3 797.67 265.89 Error: Treatment:Rat:Liver Df Sum Sq Mean Sq F value Pr(F) Residuals 12 594.049.5 Error: Within Df Sum Sq Mean Sq F value Pr(F) Residuals 18 381.00 21.17 What it dont calculate the F and P for treatment? Thanks Ronaldo -- Tristezas não pagam dívidas. Nem bravatas, por falar nisso. --Millôr Fernandes Retirado de http://www.uol.com.br/millor -- | // | \\ [***] | ( õ õ ) [Ronaldo Reis Júnior] | V [UFV/DBA-Entomologia] |/ \ [36570-000 Viçosa - MG ] | /(.''`.)\ [Fone: 31-3899-4007 ] | /(: :' :)\ [EMAIL PROTECTED]] |/ (`. `'` ) \[ICQ#: 5692561 | LinuxUser#: 205366 ] |( `- ) [***] | _/ \_Powered by GNU/Debian Woody/Sarge __ 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
Re: [R] The Perils of PowerPoint
Mulholland, Tom wrote: For some reason (probably that our organisation has blocked the site) I could not see the original articles that prompted the post. I however immediately assumed that this was precipitated by Tufte and his comments about PowerPoint (I recall seeing a good example of PowerPoint on his site) http://www.edwardtufte.com/tufte/powerpoint When this first came up I recall some dispute about the comments www.sociablemedia.com/articles_dispute.htm and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. I think that's by a different Fox named Jackson, not John. It's an interesting reading, though. Duncan Murdoch Other links that are lying on my computer are In defense of PowerPoint http://www.jnd.org/dn.mss/in_defense_of_powerp.html and Does PowerPoint make you stupid? at http://www.presentations.com/presentations/delivery/article_display.jsp?vnu_content_id=1000482464 Tom -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Tim Churches Sent: Saturday, 3 September 2005 10:08 AM To: [EMAIL PROTECTED] Cc: Achim Zeileis; r-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint (Ted Harding) wrote: By the way, the Washington Post/Minneapolis Star Tribune article is somewhat reminiscent of a short (15 min) broadcast on BBC Radio 4 back on October 18 2004 15:45-16:00 called Microsoft Powerpoint and the Decline of Civilisation which explores similar themes and also frequently quotes Tufte. Unfortunately it lapsed for ever from Listen Again after the statutory week, so I can't point you to a replay. (However, I have carefully preserved the cassette recording I made). Try http://sooper.org/misc/powerpoint.mp3 (copyright law notwithstanding...) Tim 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 __ 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 __ 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
Re: [R] R: optim
On 9/6/05, Clark Allan [EMAIL PROTECTED] wrote:
hi all
i dont understand the error message that is produced by the optim
function. can anybody help???
ie:
[[1]]$message
[1] CONVERGENCE: REL_REDUCTION_OF_F = FACTR*EPSMCH
can anyone help?
That code indicates that the optimizer has declared convergence
because the relative reduction in the objective function in successive
iterates is below a tolerance. As documented in ?optim, a convergence
code of 0 indicates success
...
convergence: An integer code. '0' indicates successful convergence.
Error codes are
...
This may be counter-intuitive but it does make sense to shell
programmers. The idea is that there is only one way you can succeed
but there are many different ways of failing so you use the nonzero
codes to indicate the types of failure and the zero code, which we
usually read as FALSE in a logical context, to indicate success.
###
SK.FIT(XDATA=a,XDATAname=a,PHI1=1,v=5,vlo=2,vhi=300,phi2lo=.01)
[[1]]
[[1]]$par
[1] -0.01377906 0.83859445 0.34675230 300.
[[1]]$value
[1] 90.59185
[[1]]$counts
function gradient
53 53
[[1]]$convergence
[1] 0
[[1]]$message
[1] CONVERGENCE: REL_REDUCTION_OF_F = FACTR*EPSMCH
#
i ghave included the function used in the optim call:
SKEWMLE=function(l,DATA=XDATA,...)
{
#alpha = l[1]
#beta = l[2]
#phi2 = l[3]
#v= l[4]
phi1=PHI1
DATA-as.matrix(DATA)
fnew-function(x,y,l,...)
{
#when we do not estimate phi1
t1=(1+((y-l[1]-l[2]*x)^2)/(l[4]*l[3]^2))^(-0.5*(1+l[4]))
t2=(1+(x^2)/l[4])^(-0.5*(1+l[4]))
t3=2*((gamma(0.5*(1+l[4]))/(gamma(0.5*l[4])*sqrt(l[4]*pi)))^2)/l[3]
t1*t2*t3
}
a-double(length(DATA))
y=DATA
a=apply(y,1,function(q)
log(integrate(fnew,lower=0,upper=Inf,y=q,l=l)$value))
-sum(a)
}
__
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
__
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
Re: [R] model selection vs. H0 based testing
-Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Thomas Petzoldt Sent: 06 September 2005 06:34 Cc: [EMAIL PROTECTED]; R-Help Subject: Re: [R] model selection vs. H0 based testing Hello, I wish to thank Douglas Bates very much for clarification and pointing me to the MCMC simulation method to get p values even for cases where Wald tests are inappropriate. One question however remains when publishing statistical results: does it help readers if we combine both, - AIC based model selection *and* - null hypothesis based tests statistics or should we focus on model selection only and try to reduce the amount of tables provided? IMHO the AIC is sufficient and the null hypothesis test is not well suited to the problem. As stated by Akaike (1974, A new look at the statistical model identification, IEEE Transactions on Automatic Control 19:716-723):As was noticed by Lehman [this is the classic book on the Neyman-Pearson theory of hypothesis testing], hypothesis testing procedures are traditionally applied to the situation where actually multiple decision procedures are required. If the statistical identification procedure is considered as a decision procedure the very basic problem is the appropriate choice of the loss function. In the Neyman-Pearson theory of statistical hypothesis testing only the probabilities of rejecting and accepting the correct and incorrect hypothesis, respectively, are considered to define the loss caused by the decision. In practical situations the assumed null hypotheses are only approximations and they are almost always different from the reality. Thus the choice of the loss function in the test theory makes its practical application logically contradictory. The recongnition of this point that the hypothesis testing procedure is not adequately formulated as a procedure of approximation is very important for the development of practically useful identification procedures. Note that Akaike speaks of 'model identification' whereas now this subject are is usually referred to as 'model selection'. Ruben __ 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
[R] help.search problem
Dear Fellow R Users, I have recently come across a weird problem with help.search: help.search(tps) Error in rbind(...) : number of columns of matrices must match (see arg 8) This happens no matter what I search for... Any thoughts ? Thanks, Tolga Please follow the attached hyperlink to an important disclaimer http://www.csfb.com/legal_terms/disclaimer_europe.shtml == Please access the attached hyperlink for an important electronic communications disclaimer: http://www.csfb.com/legal_terms/disclaimer_external_email.shtml __ 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
[R] fitting distributions with R
Dear all
I've got the dataset
data:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
I know from other testing that it should be possible to fit the data with the
exponentialdistribution. I tried to get parameterestimates for the
exponentialdistribution with R, but as the values
of the parameter are very close to 0 i get into troubles. Do you know, what i
could do in order to get estimates?How do you choose the starting values? in
my opinion it should be around 1/mean(data).
#Parameterestimation with mle() with the log-likelihood funktion of the
#exponentialdistribution
library(stats4)
ll-function(beta)
{n-24
x-data2
-n*log(beta)+beta*sum(x)}
est-mle(minuslog=ll, start=list(beta=0.1))
summary(est)
#instead of a result, i get:
Error in optim(start, f, method = method, hessian = TRUE, ...) :
non-finite finite-difference value [1]
In addition: There were 50 or more warnings (use warnings() to see the first
50)
#with fitdistr() for the exponentialdistribution
library(MASS)
fitdistr(data2,densfun=dexp,start=list(rate=0.1),lower=6e-06,method=BFGS)
#instead of a result, i get
Error in optim(start, mylogfn, x = x, hessian = TRUE, ...) :
non-finite finite-difference value [1]
In addition: Warning messages:
1: bounds can only be used with method L-BFGS-B in: optim(start, mylogfn, x =
x, hessian = TRUE, ...)
2: NaNs produced in: dexp(x, 1/rate, log)
i'll be very happy for any help i can get to solve this problem
thank you!
__
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
Re: [R] fitting distributions with R
The MLE of beta is the reciprocal of the sample mean, so you don't need an
optimizer here.
Reid Huntsinger
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Nadja Riedwyl
Sent: Tuesday, September 06, 2005 9:39 AM
To: r-help@stat.math.ethz.ch
Subject: [R] fitting distributions with R
Dear all
I've got the dataset
data:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
I know from other testing that it should be possible to fit the data with
the
exponentialdistribution. I tried to get parameterestimates for the
exponentialdistribution with R, but as the values
of the parameter are very close to 0 i get into troubles. Do you know, what
i
could do in order to get estimates?How do you choose the starting values? in
my opinion it should be around 1/mean(data).
#Parameterestimation with mle() with the log-likelihood funktion of the
#exponentialdistribution
library(stats4)
ll-function(beta)
{n-24
x-data2
-n*log(beta)+beta*sum(x)}
est-mle(minuslog=ll, start=list(beta=0.1))
summary(est)
#instead of a result, i get:
Error in optim(start, f, method = method, hessian = TRUE, ...) :
non-finite finite-difference value [1]
In addition: There were 50 or more warnings (use warnings() to see the first
50)
#with fitdistr() for the exponentialdistribution
library(MASS)
fitdistr(data2,densfun=dexp,start=list(rate=0.1),lower=6e-06,method=BFGS)
#instead of a result, i get
Error in optim(start, mylogfn, x = x, hessian = TRUE, ...) :
non-finite finite-difference value [1]
In addition: Warning messages:
1: bounds can only be used with method L-BFGS-B in: optim(start, mylogfn, x
=
x, hessian = TRUE, ...)
2: NaNs produced in: dexp(x, 1/rate, log)
i'll be very happy for any help i can get to solve this problem
thank you!
__
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
__
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
Re: [R] The Perils of PowerPoint
On 06-Sep-05 Mulholland, Tom wrote: For some reason (probably that our organisation has blocked the site) I could not see the original articles that prompted the post. I however immediately assumed that this was precipitated by Tufte and his comments about PowerPoint (I recall seeing a good example of PowerPoint on his site) http://www.edwardtufte.com/tufte/powerpoint When this first came up I recall some dispute about the comments www.sociablemedia.com/articles_dispute.htm and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. Other links that are lying on my computer are In defense of PowerPoint http://www.jnd.org/dn.mss/in_defense_of_powerp.html and Does PowerPoint make you stupid? at http://www.presentations.com/presentations/delivery/ article_display.jsp?vnu_content_id=1000482464 Tom Thanks, Tom, for these pointers to interesting discussions! One must of course agree with the general comments to the effect that the quality and merits of a presentation are the result of choices made by the person who designed it, and not primarily due to the software itself. It is also true that software such as PowerPoint provides ready-made mechanisms for linking-in a great variety of content, thereby making it -- in principle -- easier for the designer to choose judiciously what would be best for the result they wish to achieve and -- in principle -- to design an outstanding presentation. It is nevertheless still true that in practice the result is often dreadful, for reasons which largely reside in the software (but which take effect by virtue of user deficiency). I tend to put this down to the provision of so-called Wizards -- in reality electronic snake-oil merchants -- the protoype of which is the dancing paper-clip masquerading as an Office Assistant. There are other resources which can have similar effects -- spell-checkers, grammar-checkers, auto-formatters which brush you aside and re-arrange your intentions and which can be difficult to evade: indeed, one can form the impression that it has been deliberately made difficult for users to ignore these things and make their own choices. In case you may wonder how I hope to bring this On-Topic, it is as follows. The result of such things is that users' thought and practice become software-led and software-driven. The software is both carrot and stick. The user is the donkey. In contrast, as software and in its implementation as a compendium of resources and documentation, R expects users to know what they are doing and to understand the rationale of the methods. R also requires users to have the capability to locate necessary inforamtion in the documentation. Indeed, one might even describe R documentation as notoriously unintrusive! So using R should educate users in thoughtful and judicious use of statistical software. The same cannot be said so wholeheartedly of S-Plus. While the latter is basically routine-equivalent to R, and the help and menu systems properly used can also encourage judicious use, there is nevertheless a superficial aspect which can seduce users into a check-box mentality; and the printed manuals strike me as both unclear and unduly prescriptive. In other words, while S-Plus may tend to attract users who do not know what to do and who expect the softare to tell them what to do (and subsequently will not know what they have done), R will not. This spartan environment is lean and healthy, so successful R users will become lean and healthy! Not donkeys, but mountain-goats. R-help is there for those who need it, and very few responses to queries have been at all superficial. Often it is clear that respondents themselves have had to think before being able to come up with an answer, and very often the response urges the questioner to think! Indeed, evidence of thought on the part of the questioner is something of a pre-requisite for getting a response. The underlying thought behind all this is that there is something of an under-current of disquiet in the statistical community about software-driven analysis, an increasingly prevalent abuse of our subject. Occasionally it comes to the surface. Crass abuses such as are encouraged by PowerPoint snake-oil and the like are obvious; but once we perceive them we can be sensitised to similar but more subtle dangers in other software. Conscious remedial effort would be a good thing, and R seems to be an excellent vehicle for it. Thanks for reading so far! Best wishes to all, Ted. E-Mail: (Ted Harding) [EMAIL PROTECTED] Fax-to-email: +44 (0)870 094 0861 Date: 06-Sep-05 Time: 14:29:26 -- XFMail -- __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting
Re: [R] help.search problem
What version of R and what operating system? What packages do you have loaded? Try utils::help.search(tps), does that work? Have you tried it in a fresh R session, i.e. start with R --vanilla. If you can't get it to work after this, report the above information plus what you get from traceback() after you get the error. Cheers Henrik Uzuner, Tolga wrote: Dear Fellow R Users, I have recently come across a weird problem with help.search: help.search(tps) Error in rbind(...) : number of columns of matrices must match (see arg 8) This happens no matter what I search for... Any thoughts ? Thanks, Tolga Please follow the attached hyperlink to an important disclaimer http://www.csfb.com/legal_terms/disclaimer_europe.shtml == Please access the attached hyperlink for an important electronic communications disclaimer: http://www.csfb.com/legal_terms/disclaimer_external_email.shtml __ 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 __ 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
Re: [R] Doubt about nested aov output
On 9/6/05, Ronaldo Reis-Jr. [EMAIL PROTECTED] wrote: Hi Spencer, Em Dom 04 Set 2005 20:31, Spencer Graves escreveu: Others may know the answer to your question, but I don't. However, since I have not seen a reply, I will offer a few comments: 1. What version of R are you using? I just tried superficially similar things with the examples in ?aov in R 2.1.1 patched and consistently got F and p values. I'm using the R version 2.1.1 on Linux Debian Version 2.1.1 (2005-06-20), ISBN 3-900051-07-0 2. My preference for this kind of thing is to use lme in library(nlme) or lmer in library(lme4). Also, I highly recommend Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). Yes, this is my preference too, but I need aov for classes. 3. If still want to use aov and are getting this problem in R 2.1.1, could you please provide this list with a small, self contained example that displays the symptoms that concern you? And PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html;. It might increase the speed and utility of replies. spencer graves I send the complete example. This is a example from the Crwaley's book (Statistical Computing: An introdution to data analysis using S-Plus. This is a classical experiment to show pseudoreplication, from Sokal and Rohlf (1995). In this experiments, It have 3 treatmens applied to 6 rats, for each rat it make 3 liver preparation and for each liver it make 2 readings of glycogen. This generated 6 pseudoreplication per rat. I'm interested on the effect os treatment on the glycogen readings. Look the R analyses: Glycogen - c(131,130,131,125,136,142,150,148,140,143,160,150,157,145,154,142,147,153,151,155,147,147,162,152,134,125,138,138,135,136,138,140,139,138,134,127) Glycogen [1] 131 130 131 125 136 142 150 148 140 143 160 150 157 145 154 142 147 153 151 [20] 155 147 147 162 152 134 125 138 138 135 136 138 140 139 138 134 127 Treatment - factor(rep(c(1,2,3),c(12,12,12))) Treatment [1] 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 Levels: 1 2 3 Rat - factor(rep(rep(c(1,2),c(6,6)),3)) Rat [1] 1 1 1 1 1 1 2 2 2 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 Levels: 1 2 Liver - factor(rep(rep(c(1,2,3),c(2,2,2)),6)) Liver [1] 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 1 1 2 2 3 3 Levels: 1 2 3 ### Model made identical to the book model - aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver)) summary(model) Error: Treatment Df Sum Sq Mean Sq Treatment 2 1557.56 778.78 Error: Treatment:Rat Df Sum Sq Mean Sq Treatment:Rat 3 797.67 265.89 Error: Treatment:Rat:Liver Df Sum Sq Mean Sq Treatment:Rat:Liver 12 594.049.5 Error: Within Df Sum Sq Mean Sq F value Pr(F) Residuals 18 381.00 21.17 ### Model made by myself, I'm interested only in Treatment effects model - aov(Glycogen~Treatment+Error(Treatment/Rat/Liver)) summary(model) Error: Treatment Df Sum Sq Mean Sq Treatment 2 1557.56 778.78 Error: Treatment:Rat Df Sum Sq Mean Sq F value Pr(F) Residuals 3 797.67 265.89 Error: Treatment:Rat:Liver Df Sum Sq Mean Sq F value Pr(F) Residuals 12 594.049.5 Error: Within Df Sum Sq Mean Sq F value Pr(F) Residuals 18 381.00 21.17 What it dont calculate the F and P for treatment? Would it be easier to do it this way? library(lme4) Loading required package: Matrix Loading required package: lattice (fm1 - lmer(Glycogen ~ Treatment + (1|Treatment:Rat) + (1|Treatment:Rat:Liver))) Linear mixed-effects model fit by REML Formula: Glycogen ~ Treatment + (1 | Treatment:Rat) + (1 | Treatment:Rat:Liver) AIC BIClogLik MLdeviance REMLdeviance 231.6213 241.1224 -109.8106234.297 219.6213 Random effects: Groups NameVariance Std.Dev. Treatment:Rat:Liver (Intercept) 14.167 3.7639 Treatment:Rat (Intercept) 36.065 6.0054 Residual21.167 4.6007 # of obs: 36, groups: Treatment:Rat:Liver, 18; Treatment:Rat, 6 Fixed effects: Estimate Std. Error DF t value Pr(|t|) (Intercept) 140.5000 4.7072 33 29.8481 2e-16 Treatment2 10.5000 6.6569 33 1.5773 0.1243 Treatment3 -5. 6.6569 33 -0.8012 0.4288 anova(fm1) Analysis of Variance Table Df Sum Sq Mean Sq Denom F value Pr(F) Treatment 2 123.993 61.996 33.000 2.929 0.06746 The degrees of freedom for the denominator are an upper bound (in this case a rather gross upper bound) so the p-value is a lower bound. It is on my To Do list to improve tthis but I have a rather long To Do list. __ R-help@stat.math.ethz.ch
Re: [R] The Perils of PowerPoint
Please, do not blame PowerPoint for a poorly prepared or delivered talk. Blame the person who developed the presentation and the person who delivered the talk. PowerPoint is a tool. It can use used well or it can be used poorly. If I may quote a once popular newspaper cartoon character, Pogo, We Have Met The Enemy and He Is Us. John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of Maryland School of Medicine Division of Gerontology Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 410-605-7119 - NOTE NEW EMAIL ADDRESS: [EMAIL PROTECTED] Mulholland, Tom [EMAIL PROTECTED] 09/06 2:26 AM For some reason (probably that our organisation has blocked the site) I could not see the original articles that prompted the post. I however immediately assumed that this was precipitated by Tufte and his comments about PowerPoint (I recall seeing a good example of PowerPoint on his site) http://www.edwardtufte.com/tufte/powerpoint When this first came up I recall some dispute about the comments www.sociablemedia.com/articles_dispute.htm and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. Other links that are lying on my computer are In defense of PowerPoint http://www.jnd.org/dn.mss/in_defense_of_powerp.html and Does PowerPoint make you stupid? at http://www.presentations.com/presentations/delivery/article_display.jsp?vnu_content_id=1000482464 Tom -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Tim Churches Sent: Saturday, 3 September 2005 10:08 AM To: [EMAIL PROTECTED] Cc: Achim Zeileis; r-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint (Ted Harding) wrote: By the way, the Washington Post/Minneapolis Star Tribune article is somewhat reminiscent of a short (15 min) broadcast on BBC Radio 4 back on October 18 2004 15:45-16:00 called Microsoft Powerpoint and the Decline of Civilisation which explores similar themes and also frequently quotes Tufte. Unfortunately it lapsed for ever from Listen Again after the statutory week, so I can't point you to a replay. (However, I have carefully preserved the cassette recording I made). Try http://sooper.org/misc/powerpoint.mp3 (copyright law notwithstanding...) Tim 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 __ 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 __ 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
Re: [R] help.search problem
Hi there, I am using 2.0.1 . However, I was not having this problem with this version of R when I first installed it and started using it. Thanks for your suggestion, I tried it, but that doesn't work either: help.search(tps) Error in rbind(...) : number of columns of matrices must match (see arg 8) utils::help.search(tps) Error in rbind(...) : number of columns of matrices must match (see arg 8) Traceback results below: Convert Sweave Syntax, Sweave Driver Utilities, Find Objects by (Partial) Name, Browse Objects in Environment, Load URL into a WWW Browser, Send a Bug Report, Send output to a character string or file, Writing Package CITATION Files, Citing R and R Packages in Publications, Close a Socket, Compare Two Package Version Numbers, Data Sets, Spreadsheet Interface for Entering Data, Post-Mortem Debugging, Demonstrations of R Functionality, Download File from the Internet, Invoke a Text Editor, Edit Data Frames and Matrices, Run an Examples Section from the Online Help, Edit One or More Files, Fix an Object, Retrieve an R Object, Including from a Namespace, Utility functions for Developing Namespaces, Get An S3 Method, Return the First or Last Part of an Object, Documentation, Search the Help System, Hypertext Documentation, Search Indices for Help Files, Find Installed Packages, List Objects and their Structure, Create a Socket Connection, Menu Interaction Function, List Methods for S3 Generic Functions or Classes, Report the Space Allocated for an Object, Create a skeleton for a new package, Package Description, Package Management Tools, Invoke a Pager on an R Object, Person Names and Contact Information, Produce Prototype of an R Documentation File, Generate a Shell for Documentation of Data Sets, Read fixed-format data, Read Fixed Width Format Files, Read from or Write to a Socket, Browsing after an Error, Remove Installed Packages, Load or Save or Display the Commands History, Collect Information About the Current R Session, Compactly Display the Structure of an Arbitrary R Object, Summarise Output of R Profiler, Converting R Objects to BibTeX or LaTeX, Download Packages from CRAN, Display a text URL, Defunct Functions in Package utils, Deprecated Functions in Package utils, View or List Vignettes, Batch Execution of R, DLL Version Information, Install Add-on Packages from Sources, Remove Add-on Packages, R for Windows Configuration, Build a DLL for Dynamic Loading, Choose a List of Files Interactively, Read/Write Text to/from the Windows Clipboard, Get a Windows Handle, Update HTML documentation files, Report on Memory Allocation, Select Items from a List, Set or get the Window Title, Dialog Boxes under Windows, User Menus under Windows, Auxiliary Functions for the Windows Port, build, Rprof, Rtangle, RweaveLatex, Sweave, SweaveSyntConv, SweaveUtils, apropos, browseEnv, browseURL, bug.report, capture.output, citEntry, citation, close.socket, compareVersion, data, data.entry, debugger, demo, download.file, edit, edit.data.frame, example, file.edit, fix, getAnywhere, assignInNamespace, getS3method, head, help, help.search, help.start, index.search, installed.packages, ls.str, make.socket, menu, methods, object.size, package.skeleton, packageDescription, packageStatus, page, person, prompt, promptData, read.fortran, read.fwf, read.socket, recover, remove.packages, loadhistory, sessionInfo, str, summaryRprof, toLatex, update.packages, url.show, utils-defunct, utils-deprecated, vignette, BATCH, DLL.version, INSTALL, REMOVE, Rconsole, SHLIB, choose.files, readClipboard, getWindowsHandle, link.html.help, memory.size, select.list, setWindowTitle, winDialog, winMenuAdd, flush.console)) 2: do.call(rbind, dbMat[, 1]) 1: utils::help.search(tps) Please follow the attached hyperlink to an important disclaimer http://www.csfb.com/legal_terms/disclaimer_europe.shtml -Original Message- From: Henrik Bengtsson [mailto:[EMAIL PROTECTED] Sent: 06 September 2005 15:29 To: Uzuner, Tolga Cc: 'r-help@stat.math.ethz.ch' Subject: Re: [R] help.search problem What version of R and what operating system? What packages do you have loaded? Try utils::help.search(tps), does that work? Have you tried it in a fresh R session, i.e. start with R --vanilla. If you can't get it to work after this, report the above information plus what you get from traceback() after you get the error. Cheers Henrik Uzuner, Tolga wrote: Dear Fellow R Users, I have recently come across a weird problem with help.search: help.search(tps) Error in rbind(...) : number of columns of
Re: [R] fitting distributions with R
On 06-Sep-05 Huntsinger, Reid wrote:
The MLE of beta is the reciprocal of the sample mean, so you
don't need an optimizer here.
Reid Huntsinger
While that is true (and Naja clearly knew this), nevertheless
one expects that using an optimiser should also work. Nadja's
observations need an explanation.
If things don't behave as expected, it is worth while embedding
debug prints so as to monitor what is going on internally (as
fas as one can). In this case, if one modifies Nadja's ll
function to
ll-function(beta){
n-24
x-data2
temp-(-n*log(beta)+beta*sum(x))
print(temp)
temp
}
and re-runs 'mle', one sees that while there are some numerical
values in the output, there are many NaNs. Also, given the
warning message and the advice to look at warnings(), one
learns that NaNs produced in: log(x) repeatedly. This very
strongly suggests that attempts have been made to take logs
of negative numbers which in trun suggests that the method
of computing the next approximation readily takes the value
of beta outside the valid range of beta 0.
Now is the time to look at ?mle, which says that the default
method is BGFS for which see optim. Under ?optim we learn
that BGFS is a quasi-Newton method. Such methods work by
calculating a local tangent to the derivative function and
extrapolating this until it meets the beta-axis, and this can
easily take the estimate outside admissible ranges (try using
Newton-Raphson to solve sqrt(x) = 0).
However, a related method available for 'optim' is L-BFGS-B
which allows _box constraints_, that is each variable can be
given a lower and/or upper bound. The initial value must satisfy
the constraints. This can be set in a parameter for 'mle'.
So now you can try something like
est-mle(minuslog=ll, start=list(beta=0.1),
method=L-BFGS-B, lower=10*(.Machine$double.eps))
and now the trace-prints show a series of numbers, with no NaNs,
so clearly we are getting somewhere (and have identified and
dealt with at least one aspect of the problem). However, observing
the prints, one sees that after an initial trend to convergence
there is a tendency to oscillate between values in the neighbouhood
of beta=360 and values in the neighbourhood of beta=800, finally
failing when two successive values 360.6573 are printed, which
in turn suggests that an attempt is made to comuted a gradient
from identical points. So clearly there is something not right
about how the method works for this particular problem (which,
as a statistical estimation problem, could hardly be simpler!).
Now, ?optim has, at the end, a Note to the effect that the
default method (admittedly Nelder-Mead, which is not relevant
to the above) may not work well and suggests using 'optimize'
instead. So let's try 'optimize' anyway.
Now, with
optimize(ll,lower=10*(.Machine$double.eps),upper=1e10)
we get a clean set of debug-prints, and convergence to
beta = 5.881105e-05
with minimum 'll' equal to 254.6480.
Now compare with the known MLE which is
beta = 1/mean(data2) = 6.766491e-05
giving
ll(1/mean(data2)) = 254.4226,
So clearly, now, using 'optimise' instead of 'optim' which
is what 'mle' uses, we are now in the right parish. However,
there is apparently no parameter to 'mle' which would enable
us to force it to use 'optimize' rather than 'optim'!
This interesting saga, provoked by Nadja's query, now raises
an important general question: Given the simplicity of the
problem, why is the use of 'mle' so unexpectedly problematic?
While in the case of an exponential distribution (which has a
well-known analytical solution) one would not want to use 'mle'
to find the MLE (except as a test of 'mle'. perhaps), one can
easily think of other distributions, in form and behaviour very
similar to the negative exponential but without analytical solution,
for which use of 'mle' or some other optimisation routine would
be required. Such distributions could well give rise to similar
problems -- or worse: in Nadja's example,it was clear that it was
not working; in other cases, it might appear to give a result,
but the result might be very wrong and this would not be obvious.
Hmmm.
Ted.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Nadja Riedwyl
Sent: Tuesday, September 06, 2005 9:39 AM
To: r-help@stat.math.ethz.ch
Subject: [R] fitting distributions with R
Dear all
I've got the dataset
data:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;1149
1;
_ _ _ _ _ 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
I know from other testing that it should be possible to fit the data
with
the
exponentialdistribution. I tried to get parameterestimates for the
exponentialdistribution with R, but as the values
of the parameter are very close to 0 i get into troubles. Do you know,
what
i
could do in order to get estimates?How do you choose the starting
values? in
my opinion it should be around 1/mean(data).
Re: [R] simple line plots?
Ashish Ranpura [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] I still don't know how to draw each of the three line segments I need). See ?segments Could you post a small toy problem so we can see exactly what segements you're wanting to draw? efg __ 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
Re: [R] help.search problem
ToUz == Uzuner, Tolga [EMAIL PROTECTED] on Tue, 6 Sep 2005 16:35:53 +0100 writes: ToUz Hi there, ToUz I am using 2.0.1 . However, I was not having this problem with this version of R when I first installed it and started using it. yes. It only happens because of an ``incorrectly installed package'' installed somewhere in your .libPaths() and you may have ``wrong-installed'' it only recently. If you would upgrade to R 2.1.1, the problem would go away, insofar as help.start() would report about the package(s) with invalid installation. Otherwise (in R 2.0.1), it's somewhat tedious to find IIRC: You may set options(error = recover) immediately before help.start() and then inspect the pretty large matrix with the invalid entry leading to the error. The matrix has one row per package, and so you can find the invalid package. Once you know that, remove the package, and try again. [As hinted at, you should rather upgrade R] Martin Maechler ToUz Thanks for your suggestion, I tried it, but that doesn't work either: help.search(tps) ToUz Error in rbind(...) : number of columns of matrices must match (see arg 8) utils::help.search(tps) ToUz Error in rbind(...) : number of columns of matrices must match (see arg 8) ToUz Traceback results below: ToUz Convert Sweave Syntax, Sweave Driver Utilities, Find Objects by (Partial) Name, . . ToUz winDialog, winMenuAdd, flush.console)) ToUz 2: do.call(rbind, dbMat[, 1]) ToUz 1: utils::help.search(tps) ToUz -Original Message- ToUz From: Henrik Bengtsson [mailto:[EMAIL PROTECTED] ToUz Sent: 06 September 2005 15:29 ToUz To: Uzuner, Tolga ToUz Cc: 'r-help@stat.math.ethz.ch' ToUz Subject: Re: [R] help.search problem ToUz What version of R and what operating system? What packages do you have ToUz loaded? ToUz Try utils::help.search(tps), does that work? Have you tried it in a ToUz fresh R session, i.e. start with R --vanilla. ToUz If you can't get it to work after this, report the above information ToUz plus what you get from traceback() after you get the error. ToUz Cheers ToUz Henrik ToUz Uzuner, Tolga wrote: Dear Fellow R Users, I have recently come across a weird problem with help.search: help.search(tps) Error in rbind(...) : number of columns of matrices must match (see arg 8) This happens no matter what I search for... Any thoughts ? Thanks, Tolga __ 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
Re: [R] fitting distributions with R
In optim you need to set ndeps (the delta x parameter controlling the
finite-difference approximation) to a sufficiently small value (or supply
the gradient yourself to avoid finite differences, which are messy on a
restricted parameter space.) Since you expect a minimum at about 6.7e-5 the
default ndeps=1e-3 is definitely too large.
optim(par=0.1,fn=ll,method=BFGS,control=list(ndeps=1e-6))
$par
[1] 6.76644e-05
$value
[1] 254.4226
$counts
function gradient
136 18
$convergence
[1] 0
$message
NULL
There were 50 or more warnings (use warnings() to see the first 50)
The warnings are NaNs produced in: log(x) which can be avoided by making
sure the function doesn't try to take the log of something = 0, for example
change the last line to
ifelse(beta 0, -n*log(beta)+beta*sum(x), Inf)
and then optim is happy.
From mle() you can pass control to optim via ...
Reid Huntsinger
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of
[EMAIL PROTECTED]
Sent: Tuesday, September 06, 2005 11:46 AM
To: r-help@stat.math.ethz.ch
Cc: Nadja Riedwyl
Subject: Re: [R] fitting distributions with R
On 06-Sep-05 Huntsinger, Reid wrote:
The MLE of beta is the reciprocal of the sample mean, so you
don't need an optimizer here.
Reid Huntsinger
While that is true (and Naja clearly knew this), nevertheless
one expects that using an optimiser should also work. Nadja's
observations need an explanation.
If things don't behave as expected, it is worth while embedding
debug prints so as to monitor what is going on internally (as
fas as one can). In this case, if one modifies Nadja's ll
function to
ll-function(beta){
n-24
x-data2
temp-(-n*log(beta)+beta*sum(x))
print(temp)
temp
}
and re-runs 'mle', one sees that while there are some numerical
values in the output, there are many NaNs. Also, given the
warning message and the advice to look at warnings(), one
learns that NaNs produced in: log(x) repeatedly. This very
strongly suggests that attempts have been made to take logs
of negative numbers which in trun suggests that the method
of computing the next approximation readily takes the value
of beta outside the valid range of beta 0.
Now is the time to look at ?mle, which says that the default
method is BGFS for which see optim. Under ?optim we learn
that BGFS is a quasi-Newton method. Such methods work by
calculating a local tangent to the derivative function and
extrapolating this until it meets the beta-axis, and this can
easily take the estimate outside admissible ranges (try using
Newton-Raphson to solve sqrt(x) = 0).
However, a related method available for 'optim' is L-BFGS-B
which allows _box constraints_, that is each variable can be
given a lower and/or upper bound. The initial value must satisfy
the constraints. This can be set in a parameter for 'mle'.
So now you can try something like
est-mle(minuslog=ll, start=list(beta=0.1),
method=L-BFGS-B, lower=10*(.Machine$double.eps))
and now the trace-prints show a series of numbers, with no NaNs,
so clearly we are getting somewhere (and have identified and
dealt with at least one aspect of the problem). However, observing
the prints, one sees that after an initial trend to convergence
there is a tendency to oscillate between values in the neighbouhood
of beta=360 and values in the neighbourhood of beta=800, finally
failing when two successive values 360.6573 are printed, which
in turn suggests that an attempt is made to comuted a gradient
from identical points. So clearly there is something not right
about how the method works for this particular problem (which,
as a statistical estimation problem, could hardly be simpler!).
Now, ?optim has, at the end, a Note to the effect that the
default method (admittedly Nelder-Mead, which is not relevant
to the above) may not work well and suggests using 'optimize'
instead. So let's try 'optimize' anyway.
Now, with
optimize(ll,lower=10*(.Machine$double.eps),upper=1e10)
we get a clean set of debug-prints, and convergence to
beta = 5.881105e-05
with minimum 'll' equal to 254.6480.
Now compare with the known MLE which is
beta = 1/mean(data2) = 6.766491e-05
giving
ll(1/mean(data2)) = 254.4226,
So clearly, now, using 'optimise' instead of 'optim' which
is what 'mle' uses, we are now in the right parish. However,
there is apparently no parameter to 'mle' which would enable
us to force it to use 'optimize' rather than 'optim'!
This interesting saga, provoked by Nadja's query, now raises
an important general question: Given the simplicity of the
problem, why is the use of 'mle' so unexpectedly problematic?
While in the case of an exponential distribution (which has a
well-known analytical solution) one would not want to use 'mle'
to find the MLE (except as a test of 'mle'. perhaps), one can
easily think of other distributions, in form and behaviour very
similar to the negative exponential but without analytical solution,
for which use
[R] Revised shapefiles package
Now available on CRAN is a revised version of the shapefiles package for reading and writing shapefiles in R. New additions, courtesy of others, include the ability to convert a simple R data frame of points, polylines or polygons to a shp format list, which can then be written out to a shapefile with write.shp. There is also a function to convert the read.shp shp format list to a simple data frame as well. In addition, there is a basic implementation of the Douglas-Peucker polyline (and polygon) simplification routine. Also, through the help of others, there is now the ability to read and write polyline Z and polygon Z format shapefiles. The read.dbf and write.dbf functions in the foreign library are now used for dbf I/O, which significantly improves the speed. There are probably a few bugs in there that I did not catch, so please email me if you find them. Thanks. Ben Stabler Project Manager PTV America, Inc. 1128 NE 2nd St, Suite 204 Corvallis, OR 97330 541-754-6836 x205 541-754-6837 fax http://www.ptvamerica.com/ www.ptvamerica.com [[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
Re: [R] fitting distributions with R
On Tue, 6 Sep 2005, [EMAIL PROTECTED] wrote: However, a related method available for 'optim' is L-BFGS-B which allows _box constraints_, that is each variable can be given a lower and/or upper bound. The initial value must satisfy the constraints. This can be set in a parameter for 'mle'. These box constraints are really designed for situations where the boundary is a valid parameter value (so you are really doing constrained estimation) rather than situations where the boundary is an artifact of parameterisation. This interesting saga, provoked by Nadja's query, now raises an important general question: Given the simplicity of the problem, why is the use of 'mle' so unexpectedly problematic? The problem is simple only in that it is one-dimensional, and optim() doesn't take advantage of this. It is poorly scaled: since the starting value is 0.1, the maximum is at 0.6, and there is a singularity at 0, it would be helpful to specify the parscale control option to optim. The other problem is that we are using finite-difference approximations to the derivatives. These are bound to perform badly near the singularity at zero, especially in a badly scaled problem. There is a bug in that L-BFGS-B doesn't respect the bounds in computing finite-differences, but this is not going to be easy to fix (there was recent discussion on r-devel about this). If I remove the singularity by defining lll function(beta) if(beta0) 1e6 else ll(beta) and specify parscale, I get est Call: mle(minuslogl = lll, start = list(beta = 0.01), control = list(parscale = 1e-05)) Coefficients: beta 6.767725e-05 (Any parscale below 0.01 will give basically the same answer). Incidentally, the trace output may look as if it is oscillating, but that is partly an artifact of the line search that BFGS uses. The last few printed loglikelihoods are [1] 254.4226 [1] 254.4226 [1] 543.2361 [1] 542.5717 Finally, as I noted earlier, this isn't really a constrained estimation problem, it is a problem of a function defined on an open interval with a singularity at one end. In this case (in contrast to real constrained estimation problems) it might well be sensible to reparametrize. mle() then works with no problems. -thomas __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] (no subject)
my problem actually arised with fitting the data to the weibulldistribution,
where it is hard to see, if the proposed parameterestimates make sense.
data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
how am I supposed to know what starting values i have to take?
i get different parameterestimates depending on the starting values i choose,
this shouldn't be, no? how am i supposed to know, which the right estimates
should be?
library(MASS)
fitdistr(data2,densfun=dweibull,start=list(scale=2 ,shape=1 ))
scale shape
1.378874e+04 8.788857e-01
(3.842224e+03) (1.312395e-01)
fitdistr(data2,densfun=dweibull,start=list(scale=6 ,shape=2 ))
scaleshape
7.81875000 0.1250
(4.18668905) (0.01803669)
#if i use the lognormaldistribution instead, i would get the same estimates,
#no matter, what starting values i choose.
#or if i tried it so fare with mle(), i got different values depending on the
#starting values too, i use the trial and error method to find appropriate
#starting values, but i am sure, there is a clear way how to do it, no?
#shouldn't i actually get more or less the same parameterestimates with both
#methods?
library(stats4)
ll-function(alfa,beta)
+ {n-24
+ x-data2
+ -n*log(alfa)-n*log(beta)+alfa*sum(x^beta)-(beta-1)*sum(log(x))}
est-mle(minuslog=ll, start=list(alfa=10, beta=1))
There were 50 or more warnings (use warnings() to see the first 50)
summary(est)
Maximum likelihood estimation
Call:
mle(minuslogl = ll, start = list(alfa = 10, beta = 1))
Coefficients:
Estimate Std. Error
alfa 0.002530163 0.0006828505
beta 0.641873010 0.0333072184
-2 log L: 511.6957
library(stats4)
ll-function(alfa,beta)
+ {n-24
+ x-data2
+ -n*log(alfa)-n*log(beta)+alfa*sum(x^beta)-(beta-1)*sum(log(x))}
est-mle(minuslog=ll, start=list(alfa=5, beta=17))
There were 50 or more warnings (use warnings() to see the first 50)
summary(est)
Maximum likelihood estimation
Call:
mle(minuslogl = ll, start = list(alfa = 5, beta = 17))
Coefficients:
Estimate Std. Error
alfa 0.002143305 0.000378592
beta 0.660359789 0.026433665
-2 log L: 511.1296
thank you very much for all your comments, it really helps me to get further!
Nadja
__
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
Re: [R] (no subject)
Dear Nadja,
if the loglikelihood function has various local maxima, the result
may depend on the starting values. This is not unusual. The best estimator
is the one with the maximum loglikelihood, i.e., the smallest value of
-2 log L in the mle output. (Unfortunately, it seems that the
loglikelihood value is not accessible using fitdistr - you would have to
implement the loglikelihood function on you own.)
You could use a lot of starting values, for example generated by some
random mechanism, and take the best estimator.
If you want a single good starting value, you could try to fit a Weibull
distribution by eye and trial-and error to the histogram and use the
corresponding parameters.
Best,
Christian
PS: Please use informative subject lines.
On Tue, 6 Sep 2005, Nadja Riedwyl wrote:
my problem actually arised with fitting the data to the weibulldistribution,
where it is hard to see, if the proposed parameterestimates make sense.
data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
how am I supposed to know what starting values i have to take?
i get different parameterestimates depending on the starting values i choose,
this shouldn't be, no? how am i supposed to know, which the right estimates
should be?
library(MASS)
fitdistr(data2,densfun=dweibull,start=list(scale=2 ,shape=1 ))
scale shape
1.378874e+04 8.788857e-01
(3.842224e+03) (1.312395e-01)
fitdistr(data2,densfun=dweibull,start=list(scale=6 ,shape=2 ))
scaleshape
7.81875000 0.1250
(4.18668905) (0.01803669)
#if i use the lognormaldistribution instead, i would get the same estimates,
#no matter, what starting values i choose.
#or if i tried it so fare with mle(), i got different values depending on the
#starting values too, i use the trial and error method to find appropriate
#starting values, but i am sure, there is a clear way how to do it, no?
#shouldn't i actually get more or less the same parameterestimates with both
#methods?
library(stats4)
ll-function(alfa,beta)
+ {n-24
+ x-data2
+ -n*log(alfa)-n*log(beta)+alfa*sum(x^beta)-(beta-1)*sum(log(x))}
est-mle(minuslog=ll, start=list(alfa=10, beta=1))
There were 50 or more warnings (use warnings() to see the first 50)
summary(est)
Maximum likelihood estimation
Call:
mle(minuslogl = ll, start = list(alfa = 10, beta = 1))
Coefficients:
Estimate Std. Error
alfa 0.002530163 0.0006828505
beta 0.641873010 0.0333072184
-2 log L: 511.6957
library(stats4)
ll-function(alfa,beta)
+ {n-24
+ x-data2
+ -n*log(alfa)-n*log(beta)+alfa*sum(x^beta)-(beta-1)*sum(log(x))}
est-mle(minuslog=ll, start=list(alfa=5, beta=17))
There were 50 or more warnings (use warnings() to see the first 50)
summary(est)
Maximum likelihood estimation
Call:
mle(minuslogl = ll, start = list(alfa = 5, beta = 17))
Coefficients:
Estimate Std. Error
alfa 0.002143305 0.000378592
beta 0.660359789 0.026433665
-2 log L: 511.1296
thank you very much for all your comments, it really helps me to get further!
Nadja
__
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
*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
[EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakche
__
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
Re: [R] (no subject)
-Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Nadja Riedwyl Sent: Tuesday, September 06, 2005 10:22 AM To: r-help@stat.math.ethz.ch Subject: [R] (no subject) my problem actually arised with fitting the data to the weibulldistribution, where it is hard to see, if the proposed parameterestimates make sense. data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;145 42;694;11491; 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334 how am I supposed to know what starting values i have to take? i get different parameterestimates depending on the starting values i choose, this shouldn't be, no? how am i supposed to know, which the right estimates should be? This is a general issue with all (gradient-based) optimization methods when the response to be optimized has many local optima and/or is poorly conditioned. As Doug Bates and others have often remarked, finding good starting values is an art that is often problem-specific. Ditto for good parameterizations. There is no universal magic answer. In many respects, this is the monster hiding in the closet of many of the complex modeling methods being proposed in statistics and other disciplines: when the response function to be optimized is a nonlinear function of many parameters, convergence may be difficult to achieve. Presumably stochastic optimization methods like simulated annealing and mcmc are less susceptible to such problems, but they pay a large efficiency price to be so. Cheers, -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] The Perils of PowerPoint
And thus to that 'New Age' Management Role, that of the Professional PowePoint Ranger. He (invariably he) who culls the fruits of the labours of others to present in ever more slick PowerPoint compendia, whilst never sullying their hands with 'real' work. 8¬ Mike -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of bogdan romocea Sent: 06 September 2005 18:43 To: R-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint I don't understand why there's so much discussion on PowerPoint. IMHO, that can only obscure the real thing: - The Perils of Miscommunication - The Perils of Not Taking Responsibility (if PowerPoint is to blame for X, then who's to blame for choosing and using PowerPoint in the first place?) - The Perils of Being an Idiot - and so on. (I'm in grave danger here, and also responsible for using R.) -Original Message- From: Mulholland, Tom [mailto:[EMAIL PROTECTED] Sent: Tuesday, September 06, 2005 2:27 AM Cc: Achim Zeileis; r-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint For some reason (probably that our organisation has blocked the site) I could not see the original articles that prompted the post. I however immediately assumed that this was precipitated by Tufte and his comments about PowerPoint (I recall seeing a good example of PowerPoint on his site) http://www.edwardtufte.com/tufte/powerpoint When this first came up I recall some dispute about the comments www.sociablemedia.com/articles_dispute.htm and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. Other links that are lying on my computer are In defense of PowerPoint http://www.jnd.org/dn.mss/in_defense_of_powerp.html and Does PowerPoint make you stupid? at http://www.presentations.com/presentations/delivery/article_di splay.jsp?vnu_content_id=1000482464 Tom -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Tim Churches Sent: Saturday, 3 September 2005 10:08 AM To: [EMAIL PROTECTED] Cc: Achim Zeileis; r-help@stat.math.ethz.ch Subject: Re: [R] The Perils of PowerPoint (Ted Harding) wrote: By the way, the Washington Post/Minneapolis Star Tribune article is somewhat reminiscent of a short (15 min) broadcast on BBC Radio 4 back on October 18 2004 15:45-16:00 called Microsoft Powerpoint and the Decline of Civilisation which explores similar themes and also frequently quotes Tufte. Unfortunately it lapsed for ever from Listen Again after the statutory week, so I can't point you to a replay. (However, I have carefully preserved the cassette recording I made). Try http://sooper.org/misc/powerpoint.mp3 (copyright law notwithstanding...) Tim 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 __ 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 __ 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 __ 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
Re: [R] The Perils of PowerPoint
Mike Waters wrote: And thus to that 'New Age' Management Role, that of the Professional PowePoint Ranger. He (invariably he) who culls the fruits of the labours of others to present in ever more slick PowerPoint compendia, whilst never sullying their hands with 'real' work. In academia they're known as professors. Bob -- Bob O'Hara Department of Mathematics and Statistics P.O. Box 68 (Gustaf Hällströmin katu 2b) FIN-00014 University of Helsinki Finland Telephone: +358-9-191 51479 Mobile: +358 50 599 0540 Fax: +358-9-191 51400 WWW: http://www.RNI.Helsinki.FI/~boh/ Journal of Negative Results - EEB: www.jnr-eeb.org __ 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
[R] Predicting responses using ace
Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x - runif(20, 0, 1) xnew - runif(2000, 0, 1) y - sin(x) a - ppr(x, y, 2) ynew - predict(ppr, xnew) Any help would be much appretiated, Thanks in advance, Luis Pineda __ 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
Re: [R] Spacing and margins in plot
You can do this with the 'mgp' argument to par() (see ?par). For example, I find par(mgp=c(2, 0.75, 0)) (which puts the axis label on line 2 and the axis values on line 0.75) nicely tightens up the space around a plot. Rich Raubertas -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Earl F. Glynn Sent: Thursday, September 01, 2005 11:14 AM To: r-help@stat.math.ethz.ch Subject: Re: [R] Spacing and margins in plot Chris Wallace [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED] how about plot(..., xlab=) title(xlab=label text, line=2) Yes, Chris, I like your idea, especially when I can fix both X and Y axes at the same time: plot(0, xlab=,ylab=) title(xlab=X axis, ylab=Y axis, line=2) I'd prefer a way to set the axis title line at the same time I change the mar parameters, but it's not a big deal. Thanks. efg __ 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 __ 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
[R] R Cocoa GUI assumes Japanese locale
After installing the latest binary for OS X, the R Cocoa GUI provides output in the console in Japanese only. I would prefer the output to be in English, but cannot figure out how to change the setting. If I start R in a terminal window, output is in English. Version is R Cocoa GUI 1.12 (1622), S.M.Iacus S.Urbanek. Thanks for any help. Jacob Etches Doctoral candidate, Epidemiology Department of Public Health Sciences University of Toronto Faculty of Medicine Research Associate Institute for Work Health 800-481 University Ave. Toronto, ON M5G 2E9 416.927.2027x2290 www.iwh.on.ca __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] LV path analysis with PLS (was Re: PLSR: model notation and reliabilities)
On Wed, Aug 31, 2005 at 12:31:29PM +0300, I.Ioannou wrote: On Mon, Aug 29, 2005 at 08:08:53AM +0200, Bj?rn-Helge Mevik wrote: It seems to me that what you are looking for, is some sort of structured equation models (? la Lisrel). The pls package implements --snipped-- and the explained variance seem to be ok, but I'm afraid that this is not my case. I thought that plsr should be used to perform --snipped-- Well, I should had asked : Is there a way to use plsr to perform (or another R package that implements) latent variables path analysis with partial least-squares estimation, i.e. the algorithm that was implemented in the old DOS lvpls program ? (http://kiptron.psyc.virginia.edu/Programs/lvplsmanual.pdf) TIA Ioannis Ioannou __ 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
Re: [R] The Perils of PowerPoint
I incorrectly relied upon my memory ... and that John Fox did something http://ils.unc.edu/~jfox/powerpoint/introduction.html that I enjoyed reading. The work is that of Jackson Fox Tom __ 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
Re: [R] Predicting responses using ace
Luis Pineda wrote: Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x - runif(20, 0, 1) xnew - runif(2000, 0, 1) y - sin(x) a - ppr(x, y, 2) ynew - predict(ppr, xnew) Any help would be much appretiated, Thanks in advance, Luis Pineda __ 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 Look at the areg.boot function in the Hmisc package, and its associated predict method. -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] convergence for proportional odds model
liu abc [EMAIL PROTECTED] wrote: I am using proportional odds model for ordinal responses in dose-response experiments. For some samll data, SAS can successfully provide estimators of the parameters, but the built-in function polr() in R fails. Would you like to tell me how to make some change so I can use polr() to obtain the estimators? Or anyone can give me a hint about the conditions for the existance of MLE in such a simple case? By the way, for the variable resp which must be ordered factor, how can I do it? Thanks a lot. Guohui The following is one example I used both in SAS and R. in R: library(MASS) dose.resp = matrix( c(1,1,1,1,2,2,2,3,3,3, 2,2,3,3,4,4,5,4,5,5), ncol=2) colnames(dose.resp)= c(resp, dose) polr( factor(resp, ordered=T)~dose, data=dose.resp) #Error in optim(start, fmin, gmin, method = BFGS, hessian = Hess, ...) : # initial value in 'vmmin' is not finite It seems to be the starting values. Using lrm() from the Design package gave dose.resp - as.data.frame(dose.resp) dose.resp$resp - factor(dose.resp$resp) library(Design) lrm(resp ~ dose, data=dose.resp) Obs Max Deriv Model L.R. d.f. P CDxy 10 6e-06 11.43 1 7e-04 0.909 0.818 Gamma Tau-a R2 Brier 0.9310.6 0.768 0.014 CoefS.E. Wald Z P y=2 -10.904 5.137 -2.12 0.0338 y=3 -14.336 6.287 -2.28 0.0226 dose 3.160 1.399 2.26 0.0239 and giving polr starting values: print(m1 - polr(resp ~ dose, data=dose.resp, start=c(-1, -4, 3))) Call: polr(formula = resp ~ dose, data = dose.resp, start = c(-1, -4, 3)) Coefficients: dose 3.158911 Intercepts: 1|2 2|3 10.90172 14.33296 Residual Deviance: 10.34367 AIC: 16.34367 Even then, summary(m1) gives the same problem (as it refits). There is separation in the data, of course, but I presume the ordinality gives some extra information. David Duffy. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Sorting Text Frames
[Using 2.0.1 under Windows XP] There are a few pages on the internet that list equivalents of thank you in many languages. I downloaded one from a Google search and I thought that it would be interesting and a good R exercise to sort the file into the order of the expressions, rather than the languages. I tidied up the web page and got it into the format that it was nearly in: Language Name in columns 1-43, the expression in the remaining columns. Then I read it in: thanks - read.fwf(C:\\Files\\Reading\\thankyou.txt, c(43,37)) thanks[1:4,] V1V2 1 Abenaki (Maine USA, Montreal Canada)Wliwni ni 2 Abenaki (Maine USA, Montreal Canada) Wliwni 3 Abenaki (Maine USA, Montreal Canada) Oliwni 4 Achí (Baja Verapaz Guatemala) Mantiox chawe dim(thanks) [1] 12542 Now I tried sorting the frame into the order of the second column: tord - order(thanks$V2) sink(C:\\Files\\Reading\\thanks.txt) thanks[tord[1:74],] sink() This gives more or less the expected output, the file thanks.txt beginning V1 V2 145 Cahuila (United States)'\301cha-ma 862 Paipai (Mexico, USA)'Ara'ya:ikm 863 Paipai (Mexico, USA)'Ara'yai:km 864 Paipai (Mexico, USA) 'Ara'ye:km 311 Eyak (Alaska)'Awa'ahdah [you may get a bit of wrapping there!] However I don't really want just 74 lines, I would like the whole file. But if I get rid of the [1:74] or replace 74 with any larger number I get output like this, with no second column: V1 145 Cahuila (United States) 862 Paipai (Mexico, USA) 863 Paipai (Mexico, USA) 864 Paipai (Mexico, USA) 311 Eyak (Alaska) Does anyone know what is going on? Tusen tak in advance, in fact 1254 tak in advance! Murray Jorgensen -- Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: [EMAIL PROTECTED]Fax 7 838 4155 Phone +64 7 838 4773 wk Home +64 7 825 0441 Mobile 021 1395 862 __ 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
[R] Lattice key seems to ignore the key list
I've never had this problem before and can't see what could be different from other times I've used keys with lattice. It appears that auto.key is being taken as TRUE when I specify a key list. The list I specify seems to be ignored. Where can I place a browser to figure out what is going on? Having made a list key.symbol from trellis.par.get, and specified a scales list and a between list, and a formula object (form), I use xyplot like this: xyplot(form, data = xx, groups = Entry, layout = c(8,8, 1), par.strip.text = list(cex = .65), between = between, scales = scales, panel = function(x, y, ...) panel.superpose(x, y, ...), key = list(points = Rows(key.symbol, 1:4), text = list(levels(xx$Entry), space = right, columns = 1)) ) What is implied in there that would set auto.key to TRUE? The space and columns part of the list seems to be ignored and the autokey values substituted. Ideas, please. Thanks. -- Patrick Connolly HortResearch Mt Albert Auckland New Zealand Ph: +64-9 815 4200 x 7188 ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~ I have the world`s largest collection of seashells. I keep it on all the beaches of the world ... Perhaps you`ve seen it. ---Steven Wright ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~ __ 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
[R] (no subject)
hi， Is it possible to draw a string text in a rectangle according the width of this rectangle? that is, the fontsize of this string text can be adjusted according the width of the rectangle. How to set the cex parameter in text function? text (x, y = NULL, labels = seq(along = x), adj = NULL, pos = NULL, offset = 0.5, vfont = NULL, cex = 1, col = NULL, font = NULL, xpd = NULL, ...) thanks! = Salang [EMAIL PROTECTED] Tel: 021-64363311-123 Shanghai Center for Bioinformatics Technology Floor 12th,100# QinZhou Road Shanghai,China,200235 __ 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
[R] Leading in line-wrapped Lattice value and panel labels
Version 2.1.1 Platforms: all What is the trellis parameter (or is there a trellis parameter) to set the leading (the gap between lines) when long axis values labels or panel header labels wrap over more than one line? By default, there is a huge gap between lines, and much looking and experimentation has not revealed to me a suitable parameter to adjust this. Tim 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
