similar to: about Runtime Error

Full_Name: Lloyd Lubet Version: 2.4.1rc OS: XP Submission from: (NULL) (65.19.17.17) Dear Andrew, I am trying to learn gibbs sampling and Metropolis. When I run your gibbs version of multiple linear regression my session crashes. I have trimmed the dataframe and set my object.size = 1 gigB. Despite my best efforts it still crashes while advising me to contact the MCMC Pack developement team.

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

Dear listers, Am currently using MCMC approaches to estimate some parameters of my model. One parameter has to be updated using a tuned gamma distribution. So at each iteration I estimate the mean and variance of the density of the gamma approximation using "vmmin" (i also supply the gradient argument). For moderate replications the procedure works, but if I increase them R crashes.

I wrote a DLL in C that does some MCMC stuff. It is compiled using Borland's C++ Builder, version 3.0 (build 3.70) on a Windows 98 machine. The DLL loads and runs just fine. But then if I subsequently call R's plot() function, I get an illegal operation message and R crashes. In fact, I've found that this happens even if I merely load the DLL, don't ever run it, and then try to

Hi All: Recently I am researching my dissertation about the quantile model selection by bayesian approach. I have the dependent variable(return) and 16 independent variables and I need to select the best variable for each quantile of return. And the method I used is the bayesian approach, which is based on calculating the posterior distibution of model identifier. In other words, I need to obtain

Full_Name: Xin Tian Version: 1.5.0 or 1.4.0 OS: windows 2000 Submission from: (NULL) (165.230.240.114) I tried to install R 1.5.0 or R 1.4.0 to my PC with windows2000. After installation, whenever I clicked R icon, it returned to me an error message: "Rgui.exe has generated errors and will be closed by windows. You will need to restart the program. An error log is being created."

Hi there dear R users, Does anyone have any idea what the following error means and how to sort it out? Runtime Error! Program: C\Program Files\R\R-2.9.0\bin\Rgui.exe This application has requested the Runtime to terminate it in an unusual way. Please contact the application’s support team for more information. Here is the story: Running the same code, sometimes the error happens and other

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 =

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

I have been checking my package coda with the current R-devel using "R CMD check". As usual, this has uncovered a large number of errors and inconsistencies in my documentation, for which I am very grateful. The only problem I have is with code/documentation mismatches when I have written a method for a generic function, e.g. * checking for code/documentation mismatches ... WARNING

Hello, I am doing mcmc=10000 simulations from a posterior distribution of the parameters of a mixture of K=6 normal densities. I have mcmc by K matrices simMeans, simVars and simWeights containing the simulation output: one row for each simulation, one column for each normal component of the mixture. One thing I would like to do is a plot of the posterior predictive density. In order to do that

Dear List members, I am using R to generate MCMC time series plots. This is the code I use; however, everytime an error message will come out saying could not find function "plot.mcmc." I have coda package and Lattice package installed. Does anyone know what may get wrong here? Thanks so much for your suggestions. Hongli Li *library (coda) dat1=read.csv("Itemtime.csv")

Dear R users. I'm trying to fit a generalised linear spatial mode using the geoRglm package. To do so, I'm preparing my data (geodata) as follow: geoData9093 = as.geodata(data9093, coords.col= 17:18, data.col=15,* covar.col=16*) where covar.col is a factor variable (years in this case 90-91-92-93)). Then I run the model as follow: / model.5 = list(cov.pars=c(1,1),

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'm trying to use a contributed package (rmetasim) to generate simulated genetic datasets. My scripts work fine when I run them on a Sun workstation running Solaris 7 and when I run them on a ~4 year old laptop PC that I have. However, when I run them on my new laptop (Dell Latitude D410 purchased in August 2005), the simulation will run for a short (variable) period of time, then R

Hello, I tryed to use the MCMC pack, particularly the function MCMCirtKd to simulate the posterior distribution in a multidimensional IRT model. The code I used is: posterior1 <- MCMCirtKd(Y, dimensions=2, item.constraints=list("V2"=list(3,0)), burnin = 1000, mcmc = 10000, thin=1, verbose = 1, seed = NA, alphabeta.start = NA, b0 = 0, B0=0, store.item = FALSE,

Greetings glmmADMB function users, I am trying to run a series of models using the glmmADMB function with several different distribution families (e.g., poisson, negbinom). I am using a Optiplex 790 PC with Windows 7, 16.0 GB of RAM and a 64-bit operating system. I am running R version 2.15.0 and started out using the most recent version of glmmADMB (I believe version 7.2.15). My data is zero

I know of no existing functions for estimating the parameters of this model using MCMC or MML. Many years ago, I wrote code to estimate this model using marginal maximum likelihood. I wrote this based on the using nlminb and gauss-hermite quadrature points from statmod. I could not find that code to share with you, but I do have code for estimating the 3PL in this way and you could modify the

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

I have been running a Gibbs Sampler to estimate levels of efficiency in the Louisiana Shrimp Industry. I created a matrix (samp) where I stored the results of each iteration for 86 variables. I run 10,000 iterations. So, the matrix samp is 10,000 x 86. I want to use the gelman-rubin test to check for convergence. To do that, I need at least two chains. If I run second chain with different starting