[R] Windows Front end-crash error

[Duncan Murdoch]

On Thu, 20 Jan 2005 13:16:13 -0500, "Doran, Harold" <HDoran at air.org>
wrote :

>Dear List:
>
>First, many thanks to those who offered assistance while I constructed
>code for the simulation. I think I now have code that resolves most of
>the issues I encountered with memory.
>
>While the code works perfectly for smallish datasets with small sample
>sizes, it arouses a windows-based error with samples of 5,000 and 250
>datasets. The error is a dialogue box with the following:
>
>"R for Windows terminal front-end has encountered a problem and needs to
>close.  We are sorry for the inconvenience. If you were in the middle of
>something, the information you were working on might be lost."
>
>The new code is below. Can anyone suggest whether this error is derived
>from inefficient code, or is it derived based on a windows specific
>issue that can somehow be resolved and if so, how.

It looks to me like an nlme bug.  I get the error in R-patched (built
Jan 15).  DrMingw shows this at the time of the crash:

Rgui.exe caused an Access Violation at location 01c8ae4b in module
nlme.dll Reading from location 7f1e8f18.

Registers:
eax=7f210020 ebx=00000000 ecx=01368c50 edx=ffffb1df esi=00004e20
edi=01108918
eip=01c8ae4b esp=0022d1d0 ebp=0022d208 iopl=0         nv up ei ng nz
ac po nc
cs=001b  ss=0023  ds=0023  es=0023  fs=003b  gs=0000
efl=00000296

Call stack:
01C8AE4B  nlme.dll:01C8AE4B  gls_loglik
004E5E77  R.dll:004E5E77  do_dotCode
...

I changed the loop to print some status lines, and it failed after the
first time it printed gls2...

library(MASS)
library(nlme)

set.seed(123)

mu<-c(100,150,200,250)
Sigma<-matrix(c(400,80,80,80,80,400,80,80,80,80,400,80,80,80,80,400),4,4
)
mu2<-c(0,0,0)
LE<-8^2 #Linking Error
Sigma2<-diag(LE,3)
sample.size<-5000
N<-100 #Number of datasets
#Take a single draw from VL distribution
vl.error<-mvrnorm(n=N, mu2, Sigma2)

intercept1 <- 0
slope1     <- 0
intercept2 <- 0
slope2     <- 0

for(i in 1:N){
print(i)
flush.console()
temp <- data.frame(ID=seq(1:sample.size),mvrnorm(n=sample.size,
mu,Sigma))    

temp$X5 <- temp$X1
temp$X6 <- temp$X2 + vl.error[i,1] 
temp$X7 <- temp$X3 + vl.error[i,2]
temp$X8 <- temp$X4 + vl.error[i,3] 

print("reshape...")
flush.console()

long<-reshape(temp, idvar="ID",
varying=list(c("X1","X2","X3","X4"),c("X5","X6","X7","X8")), 
v.names=c("score.1","score.2"),direction='long')

print("gls1...")
flush.console()

glsrun1 <- gls(score.1~I(time-1), data=long, 
correlation=corAR1(form=~1|ID), method='ML')

print("gls2...")
flush.console()

glsrun2 <- gls(score.2~I(time-1), data=long, 
correlation=corAR1(form=~1|ID), method='ML')

intercept1[[i]] <- glsrun1$coefficient[1]
slope1[[i]]     <- glsrun1$coefficient[2]
intercept2[[i]] <- glsrun2$coefficient[1]
slope2[[i]]     <- glsrun2$coefficient[2]
}

Hopefully this will let someone more familiar with nlme track it down.

Duncan Murdoch