[R] 'nlme' crashes R (was: Using corStruct in nlme)

[grieve at u.washington.edu]

Thanks Spencer. Here is my sessionInfo():

Version 2.3.1 (2006-06-01) 
i386-pc-mingw32 

attached base packages:
[1] "methods"   "stats"     "graphics"  "grDevices" "utils"     "datasets" 
[7] "base"     

other attached packages:
    nlme 
"3.1-75" 

On Thu, 20 Jul 2006, Spencer Graves wrote:

> 	  Thanks for providing such a self-contained example by which 'nlme' 
> crashes R.  Could you please also give us 'sessionInfo()'?  I don't have 
> time to test it myself now, but perhaps if you identify your platform, you 
> might interest someone else in checking it.
> 
> 	  I'm sorry I couldn't be more helpful.
> 	  Spencer Graves
> 
> grieve at u.washington.edu wrote:
>> I am having trouble fitting correlation structures within nlme. I would 
>> like to fit corCAR1, corGaus and corExp correlation structures to my data. 
>> I either get the error "step halving reduced below minimum in pnls step" 
>> or alternatively R crashes.
>> 
>> My dataset is similar to the CO2 example in the nlme package. The one 
>> major difference is that in my case the 'conc' steps are not the same for 
>> each 'Plant'. 
> I have replicated the problem using the CO2 data in nlme (based off of the 
> Ch08.R
> script).
>> 
>> This works (when 'conc' is the same for each 'Plant':
>> 
>> (fm1CO2.lis <- nlsList(SSasympOff, CO2))
>> (fm1CO2.nlme <- nlme(fm1CO2.lis, control = list(tolerance = 1e-2)))
>> (fm2CO2.nlme <- update(fm1CO2.nlme, random = Asym + lrc ~ 1))
>> CO2.nlme.var <- update(fm2CO2.nlme,
>>  fixed = list(Asym ~ Type * Treatment, lrc + c0 ~ 1),
>>  start = c(32.412, 0, 0, 0, -4.5603, 49.344), 
>> weights=varConstPower(fixed=list(const=0.1, power=1)), verbose=T)
>> 
>> CO2.nlme.CAR<-update(CO2.nlme.var, corr=corCAR1())
>> 
>> CO2.nlme.gauss<-update(CO2.nlme.var, 
>> correlation=corGaus(form=~as.numeric(conc)|Plant,nugget=F), data=CO2)
>> 
>> CO2.nlme.exp<-update(CO2.nlme.var, 
>> correlation=corExp(form=~as.numeric(conc)|Plant,nugget=F), data=CO2)  But, 
>> if i change each of the 'conc' numbers slightly so that they are no longer
> identical between subjects i can only get the corCAR1 correlation to work 
> while R
> crashes for both corExp and corGaus:
>> 
>> for(i in 1:length(CO2$conc)){
>>     CO2$conc[i]<-(CO2$conc[i]+rnorm(1))
>> }
>> 
>> (fm1CO2.lis <- nlsList(SSasympOff, CO2))
>> (fm1CO2.nlme <- nlme(fm1CO2.lis, control = list(tolerance = 1e-2)))
>> (fm2CO2.nlme <- update(fm1CO2.nlme, random = Asym + lrc ~ 1))
>> CO2.nlme.var <- update(fm2CO2.nlme,
>>  fixed = list(Asym ~ Type * Treatment, lrc + c0 ~ 1),
>>  start = c(32.412, 0, 0, 0, -4.5603, 49.344), 
>> weights=varConstPower(fixed=list(const=0.1, power=1)), verbose=T)
>> 
>> CO2.nlme.CAR<-update(CO2.nlme.var, corr=corCAR1())
>> 
>> CO2.nlme.gauss<-update(CO2.nlme.var, 
>> correlation=corGaus(form=~as.numeric(conc)|Plant,nugget=F), data=CO2)
>> 
>> CO2.nlme.exp<-update(CO2.nlme.var, 
>> correlation=corExp(form=~as.numeric(conc)|Plant,nugget=F), data=CO2) I 
>> have read Pinheiro & Bates (2000) and i think that it should be possible 
>> to fit these correlation structures to my data, but maybe i am mistaken.
>> 
>> I am running R 2.3.1 and have recently updated all packages.
>> 
>> Thanks,
>> Katie Grieve
>> 
>> Quantitative Ecology & Resource Management
>> University of Washington
>> 
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>