similar to: Error Message: MCMCpack and coda

Hi there, I am running MCMCpack (MCMCirt1d model) on some files (26 items x about 800 – 1200 individuals). I have a problem. When I am working on “big” files, the R program crashes. More precisely I got the following Microsoft Warning: ******************************************* Microsoft Visual C++ Runtime Library Runtime Error! Program: C:\Program Files\R\R-2.4.1\bin\Rgui.exe

Hello, thank you very much for your previous answers about the C++ code. I am interested in the application of the Gibbs Sampler in the IRT models, so in the function MCMCirt1d and MCMCirtkd. I've found the C++ source codes, as you suggested, but I cannot find anything about the Gibbs Sampler. All the files are for the Metropolis algorithm. Maybe I am not able to read them very well, by the

I'm having some problems in installing some source packages under linux. As an example, MCMCpack. An error is raised when linking: > install.packages("MCMCpack") [...] * Installing *source* package 'MCMCpack' ... checking for C++ compiler default output file name... a.out checking whether the C++ compiler works... yes checking whether we are cross compiling... no checking

I am a relatively new user to R, and I am trying to learn more about converting data in an XML document into "2-dimensional format" such as a table or array. I might eventually wish to export this data into a relational database such as SQL, and/or to work with this data within the R package. My sample XML document is located at "

A character vector with a single component consisting of a long string gets truncated with $ on the right side of the R console window. The preceding sentence, for example, assigned to 'test' by cut and paste, renders like this (window maximized, 17" monitor, 800x600, if this matters): [1] "A character vector with a single component consisting of a long string gets truncated

station month bas 190 5 0.000 190 7 1.563 190 10 0.000 190 11 0.000 202 4 18.750 202 5 18.750 202 7 6.250 202 10 4.800 202 11 3.125 198 4 18.750 198 5 31.250 198 7 3.125 198 10 3.200 198 11 12.500 205 4 0.000 205 5 0.000 205 7 0.000

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Hi everyone, I am running an ordinal probit using the Bayesian MCMCpack and I am getting an error saying "attempt for find suitable starting values failed" Here is my code: > posterior <- MCMCoprobit(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 +x9 + x10 + x11 + x12 +x13 , beta.start=c(-10, 0.05, 0.02, 0.04, 0.98, 0.61, -0.29, 0.91, -0.82, 1.34, 0.68, 0.57, 0.09, 0.5), mcmc=10000)

Hi R users, I am using the package MCMCpack and I would compute the Deviance Information Criterion for selecting models, instead of using bayes factors. I know that a similar question have been sent previously to the list by others, but I have found no response. Can somebody help me? best Giacomo

Hello Everyone Both the MCMCpack and the bayesm libraries allow us to make draws from the Inverse Wishart distribution. But I wanted to find out how exactly is the Inverse Wishart distribution parameterized in these libraries. The reason I ask is the following: Now its generally standard to express Inverse Wishart as IW(0.5 * DOF,0.5* Scale). (DOF-> Degree of freedom, Scale -> Scale

Dear R users, Thanks in advance. I am Deb, Statistician at NSW Department of Commerce, Sydney. I am using R 2.9.1 on Windows XP. This has reference to the package “MCMCpack”. My objective is to select a better model using various alternatives. I have provided here an example code from MCMCpack.pdf. The matrix of Bayes Factors is: model1 model2 model3 model1 1.000 14.08

Hi, I've been having problems getting MCMCpack installed on my Solaris 10 x86 system. I've installed gcc from opencsw.org, and, for the most part, other R packages install nicely. >From what I can gather, the build fails due to a mismatch of include files. I *think* it wants to use the include files that are contained within the MCMCpack package (but I could be wrong on this - if this

I'm completely new to R and am trying to install an add-on package for one of our faculty members. I've had no problems with most of them, but am completely stuck trying to figure out why MCMCpack won't install.. any help is VERY much appreciated!!! here's what I get when I try to install the package: * Installing *source* package 'MCMCpack' ... checking for C++ compiler

Hi, I've been testing some models with the MCMCpack library. I can run the process and get a nice model "object". I can easily see the summary and even plot it. I can't seem to figure out how to: 1) Access the final coefficients in the model 2) Turn the coefficients into a model so I can then run predictions using them. A summary command will SHOW Me the coefficients, but

Hi list, I tried to install MCMCpack to R-2.12.0, got the following error, CC -m64 -library=stlport4 -I/apps/sparcv9/R-2.12.0/lib/R/include -DSCYTHE_COMPILE_DIRECT -DSCYTHE_DEBUG=0 -DHAVE_TRUNC -DHAVE_IEEEFP_H -I/opt/csw/include -KPIC -g -c MCMCSVDreg.cc -o MCMCSVDreg.o "error.h", line 598: Error: The function "abort" must have a prototype.

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,

Hi, A question. When I run gelman.diag and gelman.plot with mcmc lists obtained from MCMCregress, the results are following. > post.R <- MCMCregress(Size~Age+Status, data = data, burnin = 5000, mcmc = 100000, + thin = 10, verbose = FALSE, beta.start = NA, sigma2.start = NA, + b0 = 0, B0 = 0, nu = 0.001, delta = 0.001) > post1.R <- MCMCregress(Size~Age+Status, data

Deal all, as MCMClogit does not allow for the specification of several chains, I have run my model 3 times with different random number seeds and differently dispersed multivariate normal priors. For example: res1 = MCMClogit(y~x,b0=0,B0=0.001,data=mydat, burnin=500, mcmc=5500, seed=1234, thin=5) res2 = MCMClogit(y~x,b0=1,B0=0.01,data=mydat, burnin=500, mcmc=5500, seed=5678, thin=5) res3 =

Hi Friends.. Well, I have setting OpenLDAP on CentOS 4.4 on a Blade Server.. I am trying of setting a cluster.. But I don't know that use: NFS or CODA.. What is you opinion? -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos/attachments/20070206/62c12ffa/attachment.html>

Hi all: The CODA package provides Geweke Diagnostic method for convergence checking. The geweke.diag in CODA returns Z-score value but not give a conclustion that it is convergence or not. So I'd like to know how small/big the magnitude of Z-score is corresponding to the convergence of a chain. That is, Doese Z-score smaller or more than *threshold *determine the convergence? If so, how big