similar to: Gibbs sampling in GLMMs: Beta testers required

Dear all; Installing the GLMMGibbs package to my Solaris Unix box, I got an compiling error: ars.c:497:10: missing terminating " character ars.c: In function `dump_arse': ars.c:498: error: parse error before "mylesj" ..... The compiling error was reported to the list on Jul 3, 2003. According to Prof. Brain Ripley this is a known problem with the package and gcc 3.3,

I getting compilation errors when trying to install GLMMGibbs (see below). I'm running R v 1.7.1 on SuSE Linux 8.2. Has anyone else had this problem? I tried it on a Win2000/R 1.5.1 combination and it worked fine. Any hints are greatly appreciated. Thank you in advance, Damien >install.packages("GLMMGibbs") trying URL `http://cran.r-project.org/src/contrib/PACKAGES'

> Date: Tue, 7 Nov 2000 17:34:37 +0000 (GMT) > From: Jonathan Myles <mylesj at icrf.icnet.uk> > > I've now got a colleague at MRC-BSU to compress it, and email it as an > attachment to my UNIX machine, where I uncompressed it and then ftp'ed > it in ascii format to my laptop. So it doesn't seem to be an ascii/bin > issue ... Is it possible to get a binary

I am trying to find a way to analyze a "simple" mixed model with two levels of a treatment, a random blocking factor, and (wait for it) negative binomial count distributions as the response variable. As far as I can tell, the currently available R offerings (glmmGibbs, glmmPQL in MASS, and Jim Lindsey's glmm code) aren't quite up to this. From what I have read (e.g.

Hi R Users: This package provides two generic functions for performing Markov chain sampling in a naive way for a user-defined target distribution, which involves only continuous variables. The function "gibbs_met" performs Gibbs sampling with each 1-dimensional distribution sampled with Metropolis update using Gaussian proposal distribution centered at the previous state. The function

hi i'm looking for a gibbs sampling algorithm for R for the case of mixture of K normals, and in particular for the case of bivariate normals. i'd be grateful if anyone could send its own R-routine, at least for the univariate case. thank you in advance matteo

I have been using lme to model data with multiple nested random effects and continuous response variables however I also have data with a binary response variable, binomial errors and multiple levels of nesting of random effects (e.g. site/block/quadrat/year), is there a package available which will do this? Jim Lindsey's package "repeated" appears to be only able to cope with 2

Dear all: I am using R to do multiple imputation for longitudinal data set. The Gibbs chain basically requires draw posterior distribution of model parameters, including the random effects. The multiple imputation requires several independent Gibbs chains. So my program structure is like: for (chain in 1:5) { # perform Gibbs sampling... for (row in 1:row.no) { b.row=some function # draw

Hello everyone, I have some binary, spatially autocorrelated data I would like to run autologistic regression on. I hope to incorporate both ordinary covariates (environmental predictors) and a spatial autocovariate in the model, ideally with a second-order neighbourhood structure. Since my computing skills are limited, I am wondering if anyone has composed an algorithm for this purpose, and

I have the following code, gibbs <-function(m,theta = 0.25, lambda =0.55, n =1){ alpha <- 1.5 beta <- 1.5 gamma <- 1.5 x<- array(0,c(m+1, 3)) x[1,1] <- theta x[1,2] <- lambda x[1,3]<- n for(t in 2:(m+1)){ x[t,1] <- rbinom(1, x[t-1,3], x[t-1,1]) x[t,2]<-rbeta(1, x[t-1,1] + alpha, x[t-1,3] - x[t-1,1] + beta) x[t,3]

I am writing a Gibbs sampler. I think it is outputting some of what I want, in that I am getting vector of several thousand values (but not 10,000) in a txt file at the end. My question is, is the error message (see below) telling me that it can't output 10,000 values (draws) because of a limitation in my memory, file size, shape etc, or that there is an error in the sampler itself? >

Hey everyone, I have read the paper by Ritter and Tanner(1992) on Griddy-Gibbs sampler and I am trying to implement it in R without much luck. I was wondering if anyone had used this or could point me to any example code. Thanks, Liz --------------------------------- [[alternative HTML version deleted]]

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

Hello All, I'd like to create diagrams for dynamic web-pages via a cgi-script that itself uses R. Sadly, I found out that the png and jpeg devices need an X-server :-( , so I cannot use these nice devices. Does any one have any experience using R for on-the-flycreation of graphics for web-pages pages? Any suggestions for workarounds? thanks very much for help, Arne -- Arne Mueller

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Dear R-users, I wondered if anyone has extended GLMMGibbs to include correlated random effects, and if so, whether they would be willing to let me use their code? Jonathan Myles has no plans to extend glmm in this manner within the foreseeable future. With thanks, Patty -- -------------------------------------------------------------------------------- Assoc Prof Patty Solomon

Hello All, I've created a view stacked barplots where some of the bars should contain a pattern such as stripes. Adjacent bars of the same stack should have the same colour but a different finnling pattern. Is R able to do that? Anyway, it's not the end of the world if not, a workaround would be to export the plot in fig format and then using xfig to make the bar filling striped,

Hello All, I've created a view stacked barplots where some of the bars should contain a pattern such as stripes. Adjacent bars of the same stack should have the same colour but a different finnling pattern. Is R able to do that? Anyway, it's not the end of the world if not, a workaround would be to export the plot in fig format and then using xfig to make the bar filling striped,

Hello, I'm trying to put a mathematical expression into a legend, but R complains about a syntax error. Basically i'd like to do this: legend.text = c(expression(x < 10), expression(x >= 10)) The manual says that one can only pass mathematical expressions to axis, text etc. but not to the legend command? Is there a workaround for this? thanks a lot for help, Arne -- Arne

Dear All, I wonder if there is a way to fit a generalized linear mixed models (for repeated binomial data) via a direct Maximum Likelihood Approach. The "glmm" in the "repeated" package (Lindsey), the "glmmPQL" in the "MASS" package (Ripley) and "glmmGIBBS" (Myle and Calyton) are not using the full maximum likelihood as I understand. The