similar to: Gibbs sampler...did it work?

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]]

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]

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 am getting a repeated error when I try to run a logistic regression in R 2.8.1 >(glm(prop1~x1,data=glm1,family=binomial("logit"),weights=nt1)) Error in model.frame.default(formula = prop1 ~ x1, data = glm1, weights = nt1, : invalid type (list) for variable 'x1' x1 is multistate categorical (3 categories). 2 of the categories have 12 observation, one has 9. Is this what

I am a pretty new R user, I am running the latest linux version on xandros, updated with some extra debian packages, and I also run the latest windows version, but prefer linux. I am having trouble downloading "bayesm", it won't do it all from any of the sites on the web, I resorted to this one, http://packages.debian.org/unstable/math/r-cran-bayesm. and got slightly further, but I

Any ideas? I certainly have X11, I have tried copying it into other directories. At present it is in /etc/X11. This is my error message. /home/user> R CMD INSTALL -l [/usr/local/R/site-library] rgl_0.81.orig.tar.gz * Installing *source* package 'rgl' ... checking for gcc... gcc -std=gnu99 checking for C compiler default output file name... a.out checking whether the C compiler

Hi all, I am trying to run rejection sampling for the quantity z11 in the function below. Unfortunately I can't simplify the function further so that z11 only appears once. Whenever I run the algorithm, R looks as if it is running it (no error messages or anything), but then nothing happens for minutes...how long should it take to run something like this in R? I have tried in in both linux

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

Sort of a warning before I start: This post may be considered to describe a rather amateurish approach to distributing software which may annoy some people, but I sincerely hope it doesn't. I've been working for some years with David Clayton on a project which started life as an S package but has now turned into an R library. It is (now) called GLMMGibbs and estimates the parameters of

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Hi Ilia. It looks like there is a hardware bug on Fermi and Kepler where TLD unconditionally uses the sampler from slot 0. This is supposedly fixed in Maxwell. What I could find internally suggests the bug wasn't present on Tesla, but let me know if your observations contradict that. The only work around is to have a sampler defined and bound. Further, be careful to have reasonable state

I have downloaded the Umacs (Universal Markov chain sampler) and submitted the following sample code from Kerman and Gelman.   s <-Sampler( J=8, sigma.y  =c(15,10,16,11,9,11,10,18),           y  =c(28, 8,-3,7,-1,1,18,12),      theta =Gibbs(theta.update,theta.init),           V =Gibbs(V.update,mu.init),         mu =Gibbs(mu.update,mu.init),         tau =Gibbs(tau.update,tau.init),       

Hi there, I wrote a slice sampler (one dimension) , After testing it, I found it working well on some standard distributions, but problematic with others. I have thought about it but really can't figure out how to improve it, so I attached the code here and hope that someone here is willing to try it out and give me some feedback. I would really appreciate it. I basicly followed

Hi, I'm having issues with what I believe is a bug in the MCMCpack's MCMCmetrop1R function. I have code that basically looks like this: posterior.sampler <- function(data, prior.mu){ log.posterior <- function(theta) log.likelihood(data, theta) + log.prior(prior.mu, theta) post.samples <- MCMCmetrop1R(log.posterior, theta.init=prior.mu, burnin=100, mcmc=1000, thin=40,

can somebody help me run this app? http://www.maizesoft.cn/msp/en/download.htm when i start the app the GUI is only a white box with the menu, but no things in it. can somebody help? there are a lot o messages like this in konsole: fixme:gdiplus:GdipDrawImagePointRectI (0x292a2b8, 0x136210, 0, 0, 0, 0, 63, 19, 2): stub fixme:gdiplus:GdipDrawImagePointRectI (0x292a2b8, 0x136408, 0, 0, 0, 0, 63,

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, This question is in the context of Tesla / Fermi generations, which have explicit bindings for textures / samplers. It might also apply to Kepler+, not quite as sure due to the bindless nature. I've been trying to understand how the TLD operation works (which is used to implement texelFetch in GLSL). It does not appear to the op takes an explicit sampler id at all (unlike all the

Hi Andy, Thanks for checking! I do see an issue on Tesla as well (at least G92, and I believe someone else reported on a GT215 or GT218). However I haven't confirmed that it's the identical issue to what I see on Fermi with quite as much certainty as what I've checked on a GF108. (For the G92, the texture buffer object test fails in the same way it does on Fermi, but there could be