[R] Inflated Array
Hi R-users! I am trying to create a what I call inflated array (maybe there is already some other name for that). It is an array that changes dinamically its dimensions, e.g. the higher the number of third dimensions, the more rows in the array. So for example the array could look like the following: , ,1 1 2 3 4 , , 2 5 6 7 8 9 10 11 12 , , 3 13 14 15 16 17 18 19 20 21 22 23 24 Has anybody a comment on how to build this in the most efficient manner (I know i could do looping)? Thanks! Hadassa __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/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] Negative Binomial: Simulation
Addition to last email: The problem basically arises also when I want to calculate (plot) the cumulative distribution of the negative binomial with the calculated parameters mu and theta! On 7/14/06, Hadassa Brunschwig <[EMAIL PROTECTED]> wrote: > Hi R-Users! > > (sorry about the last email) > I fitted a negative binomial distribution to my count data using the > function glm.nb() and obtained the calculated parameters > theta (dispersion) and mu. > > I would like to simulate values from this negative binomial distribution. > Looking at the function rnbinom() I was looking at the relationship > between the two possible parametrizations of the negative binomial and found > that for this fuction I must use: > > prob = theta/(theta+mu) and size = theta > > Theta, however, is not an integer. So how can size (which is the number of > successes) equal theta? > > I know there is a function rnegbin which does what I want. I would still > like to raise the above question (probably a more statistical one > than R). > > Thanks a lot for any comments. > > Hadassa > __ R-help@stat.math.ethz.ch 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] Negative Binomial: Simulation
Hi R-Users! (sorry about the last email) I fitted a negative binomial distribution to my count data using the function glm.nb() and obtained the calculated parameters theta (dispersion) and mu. I would like to simulate values from this negative binomial distribution. Looking at the function rnbinom() I was looking at the relationship between the two possible parametrizations of the negative binomial and found that for this fuction I must use: prob = theta/(theta+mu) and size = theta Theta, however, is not an integer. So how can size (which is the number of successes) equal theta? I know there is a function rnegbin which does what I want. I would still like to raise the above question (probably a more statistical one than R). Thanks a lot for any comments. Hadassa __ R-help@stat.math.ethz.ch 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] Negative Binomial: Simulation
Hi R-Users! I fitted a negative binomial distribution to my count data using the function glm.nb() and obtained the calculated parameters theta (dispersion) and mu. I would like to simulate values from this negative binomial distribution. Looking at the function rnbinom() I was looking at the relationship between the two possible parametrizations of the negative binomial and found that for this fuction I must use: prob = theta/(theta+mu) and size = theta Theta, however, is not an integer. So how can size (which is the number of successes) equal theta? I know there is a function rnegbin which does what I want. I would still like to raise the above question (probably a more statistical one than R). Thanks a lot for any comments. Hadassa [[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
[R] tick mark intervals
Hi everyone! This must be a common question but I have not found an answer to it in the archives yet. I am producing four plots with par(mfrow=c(2,2)). The x-axis is the same for all of them but the y-axis is different. What I would like to do is to have a different range of the y-axis and different intervals between tick marks. BUT I would like to have the same number of tick marks and I would like the y-axis to look the same. EXAMPLE (with two plots): plot1: number of tick marks = 11 interval between tick marks = 5 (i.e. tick marks at 0,5,10,15, etc.) range of y-axis = (0, 50) plot2: number of tick marks = 11 interval between tick marks = 10 (i.e. tick marks at 0,10,20,etc.) range of y-axis = (0,100) Now I can obtain the values at which there should be tick marks for each of the above plots. The problem is that when I plot them with par(mfrow=c(1,2)) I obtain the same graphical height for each y-axis but the y-axis of plot1 has no tick marks after the value of 50 which looks ugly. I would like to stretch the 50 of plot1 to where the 100 of plot2 is such that the it looks evenly distributed. But that means that an interval between tick mark 1 and 2 of plot1 (which is 5) is as long (graphically) as the interval between tick mark 1 and 2 of plot2 (which is 10). Any ideas on how to do this? Thanks a lot!! Cheers, Hadassa [[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
[R] R2WinBUGS: Comparison to WinBUGS
Hi R-Users! I know I posted the question before (see archives) but I have not been able to find the mistake. Again using R2WinBUGS and WinBUGS does not yield the same result (although to my opinion the commands are the same). The variance of the parameters is much bigger and the parameter estimates are a bit different, too. If anybody has the time and interest to get the files and data and see if he/she has the same problems, I would be happy to provide these (and to discuss it further). It seems though that it must be my mistake SOMEWHERE because nobody else reported any problems yet... Thanks. Hadassa -- Hadassa Brunschwig Birmannsgasse 10A CH-4055 Basel Switzerland Phone: +41 78 797 6065 Email: [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
Re: [R] [Fwd: R2WinBUGS: Comparison to WinBUGS]
Thanks for the tip. That was already helpful. But I am still not satisfied with
the results. I now really changed n.thin to the same I had in WinBUGS. It looks
like the commands should now be the same. However, I still get differences of
0.6 in the means of interesting parameters which should not be. The plot as well
looks completely different. While in WinBUGS I get an approximately Gaussian
posterior, this is not the case in R2WinBUGS, it is rather skewed. Does anyone
know where the problem could be? As getting a Gaussian posterior is crucial for
my work, I dont really know which results i should rely on.
Thanks a lot.
--
Hadassa Brunschwig
Birmannsgasse 10A
CH-4055 Basel
Switzerland
Phone: +41 78 797 6065
Email: [EMAIL PROTECTED]
Quoting Sibylle Sturtz <[EMAIL PROTECTED]>:
> This is due to the following:
>
> In bugs(), the default for thinning is
>
> n.thin = max(1, floor(n.chains * (n.iter - n.burnin)/1000))
>
> which is 29 for n.iter=12000 and n.burnin=2001 as in your example.
> Therefore, the number of iterations used for calculation of posterior
> values is
>
> (12000-2001)/29 = 344.7931
>
> which corresponds to the number of iterations given in your plot. If you
> specify the thinning parameter directly in bugs() it should be fine.
>
> Sibylle
>
> > Original Message
> > Subject: [R] R2WinBUGS: Comparison to WinBUGS
> > Date: Wed, 28 Sep 2005 03:55:08 -0400
> > From: Hadassa Brunschwig <[EMAIL PROTECTED]>
> > To: r-help@stat.math.ethz.ch
> >
> > Hi R-Help!
> >
> >
> > I used R2WinBUGS and WinBUGS directly on the same model just to compare.
> It
> > seems I am still making a mistake: after running the function bugs() I
> > tried to
> > plot the posteriors of the parameters by using read.bugs() to convert
> > the output
> > to an mcmc object and then plot.mcmc() to plot the densities. Using the
> > same
> > model, the same number of iterations, the same initial values and the
> > same data
> > I get completely different plots for the densities (e.g. the range of one
> > parameter in R2WinBUGS is from 0 to 8 but in WinBUGS only from 1.5 to
> > 3)??? That
> > means my results are different, too.
> > Also, on the plot it says N=345 which is not what I specified in the
> bugs()
> > function (I specified 12000 iterations).
> > Below I put some of the code I used (if that helps):
> >
> > parameters <-
> >
> c("tau","C0","st90","C0.pop","st90.pop","tau.cpop","tau.stpop","st90.pop80")
>
> >
> > inits <- inits <- function(){
> > list(tau = rep(1, 17),tau.cpop = 0.2, tau.stpop = 1)
> > }
> >
> > mcmcA <-
> >
> bugs(dataA,inits,parameters,modelA,n.chains=3,debug=T,n.iter=12000,n.burnin=2001,
>
> >
> >bugs.directory="c:/Program
> > Files/WinBUGS14",working.directory="C:/Documents and
> > Settings/Daikon/Roche/R2WinBUGS Output",codaPkg=T)
> >
> > codaA1 <- read.bugs(mcmcA[1])
> > plot(codaA1)
> >
> >
> > THANKS A LOT!!
>
> --
> Dipl.-Stat. Sibylle Sturtz
> Mathematische Statistik und biometrische Anwendungen
> Fachbereich Statistik
> Universität Dortmund
> 44221 Dortmund
> Tel.: 0231/755 4391
> FAX : 0231/755 5303
>
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[R] R2WinBUGS: Comparison to WinBUGS
Hi R-Help!
I used R2WinBUGS and WinBUGS directly on the same model just to compare. It
seems I am still making a mistake: after running the function bugs() I tried to
plot the posteriors of the parameters by using read.bugs() to convert the output
to an mcmc object and then plot.mcmc() to plot the densities. Using the same
model, the same number of iterations, the same initial values and the same data
I get completely different plots for the densities (e.g. the range of one
parameter in R2WinBUGS is from 0 to 8 but in WinBUGS only from 1.5 to 3)??? That
means my results are different, too.
Also, on the plot it says N=345 which is not what I specified in the bugs()
function (I specified 12000 iterations).
Below I put some of the code I used (if that helps):
parameters <-
c("tau","C0","st90","C0.pop","st90.pop","tau.cpop","tau.stpop","st90.pop80")
inits <- inits <- function(){
list(tau = rep(1, 17),tau.cpop = 0.2, tau.stpop = 1)
}
mcmcA <-
bugs(dataA,inits,parameters,modelA,n.chains=3,debug=T,n.iter=12000,n.burnin=2001,
bugs.directory="c:/Program
Files/WinBUGS14",working.directory="C:/Documents and
Settings/Daikon/Roche/R2WinBUGS Output",codaPkg=T)
codaA1 <- read.bugs(mcmcA[1])
plot(codaA1)
THANKS A LOT!!
--
Hadassa Brunschwig
Birmannsgasse 10A
CH-4055 Basel
Switzerland
Phone: +41 78 797 6065
Email: [EMAIL PROTECTED]
__
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Re: [R] R2WinBUGS: Data loading error
Thank you for your answer. I found out the mistake and it finally works!!
Hadassa
--
Hadassa Brunschwig
Birmannsgasse 10A
CH-4055 Basel
Switzerland
Phone: +41 78 797 6065
Email: [EMAIL PROTECTED]
Quoting Uwe Ligges <[EMAIL PROTECTED]>:
> Hadassa Brunschwig wrote:
>
> > Hi R-Help!
> >
> > I am trying to use R2WinBUGS but I get the following error message in
> WinBUGS
> > (and there must be something wrong with my R statement as I tried it
> directly in
> > WinBUGS and it worked):
> >
> > display(log)
> > check(C:/Documents and Settings/Daikon/Roche/pop_model.txt)
> > model is syntactically correct
> > data(C:/Documents and Settings/Daikon/Roche/data.txt)
> > expected key word structure
> > compile(7)
> > ...(and of course nothing works after that)
> >
> > and when I close WinBUGS i get:
> > Error in file(file, "r") : unable to open connection
> > In addition: Warning message:
> > cannot open file 'codaIndex.txt'
> >
> > Does anyone know what this 'expected key word structure' means?
> > This is my R code (and I guess my model file is ok):
> >
> > modelA <- c("C:/Documents and Settings/Daikon/Roche/pop_model.txt")
> > n <- length(unique(subsetA$subject))#number of subjects
> > nt <- 13 #number of days
> > Y <- subsetA$concentr #concentration per
> day/subject
> > t <- 1:13 #days
> > dataA <- list("n","nt","Y","t")
> > parameters <-
> c("tau","C0","st90","C0.pop","st90.pop","tau.cpop","tau.stpop")
> > inits <-
> >
>
list(tau=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),C0=5,st90=4,C0.pop=5,st90.pop=4,tau.cpop=0.2,tau.stpop=1)
> > mcmcA <-
> >
> bugs(dataA,inits,parameters,modelA,debug=T,n.chains=7,bugs.directory="c:/Program
> > Files/WinBUGS14",working.directory="C:/Documents and
> Settings/Daikon/Roche")
>
>
>
> Which versions of R, WinBUGS and R2WinBUGS?
> Your example is not reproducible for us.
>
> I'd take a look whether dimensions are OK and whether subsetA$concentr
> is in appropriate object, but without data and model file I am unable to
> help for the data part.
>
>
> For the inits part, please see ?bugs:
>
> inits: a list with n.chains elements; each element of the list is itself
> a list of starting values for the WinBUGS model, or a function creating
> (possibly random) initial values. Alternatively, if inits = NULL,
> initial values are generated by WinBUGS
>
> Looks like you want to have the same inits for each chain. In order not
> to repeat the inits 7 times, you might want to specify them simply as a
> function such as:
>
> inits <- function(){
> list(tau = rep(1, 17), C0 = 5, st90 = 4, C0.pop = 5, st90.pop = 4,
> tau.cpop = 0.2, tau.stpop = 1)
> }
>
>
> Uwe Ligges
>
>
> [Further correspondence on this particular topic, please respond to to
> the package maintainer (Sibylle) and me directly rather than to R-help.]
>
>
> >
> > Thanks so much...
> >
> > Hadassa
> >
> >
>
>
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[R] R2WinBUGS: Data loading error
Hi R-Help!
I am trying to use R2WinBUGS but I get the following error message in WinBUGS
(and there must be something wrong with my R statement as I tried it directly in
WinBUGS and it worked):
display(log)
check(C:/Documents and Settings/Daikon/Roche/pop_model.txt)
model is syntactically correct
data(C:/Documents and Settings/Daikon/Roche/data.txt)
expected key word structure
compile(7)
...(and of course nothing works after that)
and when I close WinBUGS i get:
Error in file(file, "r") : unable to open connection
In addition: Warning message:
cannot open file 'codaIndex.txt'
Does anyone know what this 'expected key word structure' means?
This is my R code (and I guess my model file is ok):
modelA <- c("C:/Documents and Settings/Daikon/Roche/pop_model.txt")
n <- length(unique(subsetA$subject))#number of subjects
nt <- 13 #number of days
Y <- subsetA$concentr #concentration per day/subject
t <- 1:13 #days
dataA <- list("n","nt","Y","t")
parameters <- c("tau","C0","st90","C0.pop","st90.pop","tau.cpop","tau.stpop")
inits <-
list(tau=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),C0=5,st90=4,C0.pop=5,st90.pop=4,tau.cpop=0.2,tau.stpop=1)
mcmcA <-
bugs(dataA,inits,parameters,modelA,debug=T,n.chains=7,bugs.directory="c:/Program
Files/WinBUGS14",working.directory="C:/Documents and Settings/Daikon/Roche")
Thanks so much...
Hadassa
--
Hadassa Brunschwig
Birmannsgasse 10A
CH-4055 Basel
Switzerland
Phone: +41 78 797 6065
Email: [EMAIL PROTECTED]
__
R-help@stat.math.ethz.ch mailing list
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[R] survreg: fitting different location parameters
Hi R-Help! My question: I have lifetime/failure data of machines with different stress levels and i think an weibull/extreme value distribution would fit this data. So I did: model1 <- survreg(Surv(lfailure)~stress,data=steel,dist="extreme") (where lfailure=log(failure)) Now I would like to do a likelihood ratio test to test the hypothesis H0: location parameters of the extreme value distribution are equal for each stress level. So in order to perform the likelihood ratio test I need the likelood of the model under HA: location parameters are not equal (i.e. each stress level has its slope and intercept). How can I do this? Thanks for any help! Hadassa __ R-help@stat.math.ethz.ch 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] adding to Trellis plot
Hello everyone (Im not sure if i already posted this problem) I have grouped data and i used a Trellis plot to show the curve of a fitted model for each group. Additionally i have a vector whose values are the highest points the curve can reach (the curve rises exponetially). Each value of the vector is the corresponding highest point for each group/plot. Now i want to show this highest point by adding to each plot a horizontal line. Obviously i should use panel.abline or something equal. How can i tell R that each value of this vector corresponds to the different plots in the Trellis plot? Thanks a lot for answers Dassy __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] function "lme"
Thanks to everyone who replied to my first problem. Here is the second one: Is the function "lme" (Mixed Model) also in a foreign library(shouldnt, as this is a basic statistical function)? I am trying to use lme in R and it replies that it couldnt find the function lme...weird... Thanks for replying! __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Importing Data
Im trying to import data from an excel sheet or a sas file to R...im not succeeding. Apparently the function read.xport for reading a SAS file doesnt exist. What do i have to type in EXACTLY to read from an excel sheet(i guess i would be using read.table?)? Thanks in advance for an answer Dassy __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
