similar to: Griddy-Gibbs sampler

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? >

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]

Hello ALL! Some times ago I started to learn and play with Bayesian stuffs. Many advice use of WinBUGS for Bayesian inference Using Gibbs Sampler. However, WinBUGS is discontinued, and now, development is under OpenBUGS. I wasn't lazy, so I installed both and tried out. In more than 90% of cases they give comparable outcome. But in few cases I got substantial differences. Recently, I read nice

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

A naive question from a non-statistician: I'm looking into running a Bayesian analysis of a model with high dimensionality. It's not a standard model (the likelihood requires a lot of code to implement), and I'm using a Linux machine. Was wondering if someone has any thoughts on what the advantages of OpenBugs are as opposed to just R (or should I be thinking WinBUGS under Wine?)?

Dear R-users (and developers), I am looking for an efficient framework to carry out parameter estimations based on MCMC (optionally with specified priors). My goal is as follow: * take ANY R-function returning a likelihood-value (this function may itself call external programmes or other code!) * run a sampler that covers the multidimensional parameter space (thus creating a posterior

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),       

Hallo, I have got an existing data frame and want to add a new column. The existing data frame was created like this: > df <- rbind( c("Fred", "Mary", 4), c("Fred", "Mary", 7), + c("Fred", "Mary", 9), c("Barney", "Liz", 3), + c("Barney", "Liz", 5) ) > df

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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

#I am putting a test together for an introductory biology class and I would like to put different cross hatching inside of each bar for the bar plot below color <- c("Brightly Colored", "Dull", "Neither") lizards <- c(277, 70, 3) liz.col <- data.frame(color, lizards) qplot(color, lizards, data=liz.col, geom="bar", ylab="Observed Matings",

Dear Wine-friends, I was wondering if any of you would have a clue around why WinBUGS (http://www.mrc-bsu.cam.ac.uk/bugs/), a nifty Markov chain Monte Carlo sampler widely used in Bayesian statistical modelling, no longer works when run through any version of WINE newer than 1.1.12. I have encountered this issue of my machines at home (which runs on Zenwalk 6.0) and work (Mandriva 2008.1) a

Hallo, I build a list by the following way: Lst = list(name="Fred", wife="Mary", no.children=3, cild.ages=c(4,7,9)) I know how I can extract the information one by one. But now I want to add a new entry which looks like name="Barney", wife="Liz", no.children=2, cild.ages=c(3,5) How can I add this information to Lst without overwriting the first entry?

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 - -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi! Has anyone gotten it working at all with Linux :) I picked one up for thiry bucks and would love to monitor it! Liz - -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.1 (Darwin) iD8DBQFD/5fEIACpLcG4dhwRAmeCAJ9+8FGXqKoOlZdkw/KFXb9n0PEemwCdHaoD NVnv7JjmBAjNsExK6WzAdnA= =pcPX - -----END PGP

I thought I had things figured out, but guess not. I have multi-user Quickbooks databases that functioned fine on a Novell server but are behaving badly on a Samba share. I have created a separate share for the Quickbook databases, users are running Win XP Pro, latest patches, and the Quickbooks application installed on the desktop. It is a multiuser version. Server is RedHat ES 3, Samba

Dear R-helpers, Hi! All. I'm doing a project which needs MCMC simulation. I wonder whether there exists related packages in R. The only one I know is a MCMCpack package. What I want to do is implementing gibbs sampling and Metropolis-Hastings Algorithm to get the posterior of hierarchical bayesian models. Thanks in advance. Jun

The smb service is not starting automatically. I can type service smb start at the prompt and it loads, and I can then connect, but its not loading automatically as it used to. Can someone point me in the right direction as what file I need to change to make it load at startup. Thanks! Liz

Hi! I'm using a large panel data, and now I have faced some difficulties with my analysis. The predictors are not normally distributed and there are quite many outliers (some of them are influential though). I have tried to change the logarythm, but i'm not sure, how to do that. I want also draw a plot picture in which logarythms of predictors x and y are changed. How could I do that?

Dear list, I'm trying to embed OpenBUGS in an R package for use of it on 64-bit Linux. In order to get the CLI working one has to compile C code contained in $OpenBUGS/Manuals/CBugs.html (copied to say CBugs.c) using gcc -m32 -o bugs CBugs.c -ldl I put the OpenBUGS distribution in the ./inst subdirectory of the package root. Where should I now put the CBugs.c and how