[R] R Crash -- R Gui crashes during MCMC iteration

[Haillie]

Hi I am posting to seek some advice regarding the R Gui 2.12.0 that keeps
freezing on my pc. 
I have been trying to run MCMC ordinal factanal code on my PC but the window
freezes everytime after 7001 iterations (total of 250000 iterations). My
operating system is window vista 64-bit with 4.0 gb of memory. 
Here is the code that I was trying to run under MCMCpack. 

## installing packages 
install.packages("MCMCpack") 
install.packages("foreign") 

## calling libraries 
library(MCMCpack) 
library(foreign) 

## opening a data set on the desktop 
setwd("C:/Users/haillie/Desktop") 
UN2009<- read.csv("UN2009.csv") 

#calling libraries 
library(reshape) 
library(car) 

colname <- names(UN2009) 
## these are thevariables I want to recode 

UN2009[colname] <- 
   lapply(UN2009[colname], 
       function(x) recode(x, recodes = "8=NA", 
           as.factor.result = TRUE, as.numeric.result = FALSE)) 
## this applies the recode functionto all the variable I wantto recode 

## Ordinalfactanal Code 
un2009<-MCMCordfactanal(~R.64.6+R.64.10+R.64.16+R.64.17+R.64.18+R.64.19+R.64.20+R.64.21+R.64.23+R.64.28+R.64.31+R.64.34+R.64.37+R.64.39+R.64.42+R.64.44+R.64.47+R.64.48+R.64.50+R.64.52+R.64.53+R.64.54+R.64.55+R.64.56+R.64.57+R.64.59+R.64.66+R.64.69+R.64.27+R.64.71+R.64.89+R.64.90+R.64.91+R.64.93+R.64.94+R.64.98+R.64.99+R.64.105+R.64.88+R.64.106+R.64.87+R.64.92+R.64.95+R.64.97+R.64.147+R.64.160+R.64.170+R.64.172+R.64.173+R.64.174+R.64.175+R.64.176+R.64.148+R.64.150+R.64.151+R.64.152+R.64.156+R.64.157+R.64.195+R.64.185+R.64.188+R.64.209+R.64.197+R.64.189+R.64.238+R.64.254+R.64.282+R.64.292+R.64.296, 
data=UN2009,lambda.constraints=list(R.64.18=list(2,"+")), factors=1,
burnin=5000, mcmc=200000, thin=40, verbose=1000, L0=0.05, store.lambda=TRUE,
store.scores=TRUE, tune=1.2) 

The system is fine until I try to run the ordinalfactanal iterations.... I
am also using the most recent version of Tinn R with R gui. not at the same
time but they share the same window space. Could this be a problem? 
I do not think the data set I am using is too big ( dimension 193, 27). 

If anyone could help me gain some insight into this problem, I would greatly
appreciate it. Thank you very much and I hope to hear from you soon. 

Sincerely, 
Haillie 
  


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