[R-sig-ME] rpt.remlLMM(y, groups) causes R to crash

[Ben Bolker]

On 14-06-06 12:28 PM, AvianResearchDivision wrote:
> Hi Ben,
> 
> Thanks for the response.  I'm sorry I didn't give you the heads up about
> r-forge.  I messed around with 'nboot' and 'npermut' by decreasing from
> their defaults of 1000 to 10 and that allowed me to run it just fine.  In
> general, what is the harm in straying away from these default parameters?
> 
> Jacob

     I don't think you've actually solved your problem this way, but you
have demonstrated that it's something having to do with a
computationally intensive workload, and not something intrinsic about
the code. That is, there's not something about running a single
bootstrap or permutation that will make your computer crash.  (The other
thing to try is using small values of nboot/npermut, but re-running the
command many times to see if you can trigger a crash.) On the other
hand, computer-crashing bugs are usually *not* deterministic in this way
-- they often depend on some haphazard or not-easily-repeatable sequence
of interactions with the operating system ...)

   My more basic question is whether you can make R crash by using the
examples with large values of nboot/npermut (in which case this is a
general issue) or not (in which case it seems like an interaction
between some quirk of your data and the software).  I haven't looked
into what npermut/nboot are doing, but they're presuming computing some
sort of simulation-based p-values/confidence intervals; if you only run
a small number of replicates, then your estimates will be very coarse.
I'm guessing that the small values of nboot/npermut in the examples are
there so that people aren't accidentally running long/slow jobs when
they try out the examples, not that these values are really recommended
for production use. It *might* be possible to get the same answers by
running a large number of commands that each run a small number of
permutation/bootstrap samples and then assembling them, but that's
likely to be tricky.

  Do you have the same kinds of problems if you run from a batch file
rather than from the Windows GUI?

  I *was* going to say that we do know of a few memory-access issues
with lme4, but now that I remember that rpt.remlLMM uses lme and not
lmer, I can't see why that would matter ...

  cheers
    Ben Bolker

> 
> 
> On Fri, Jun 6, 2014 at 10:54 AM, Ben Bolker <bbolker at gmail.com> wrote:
> 
>> On 14-06-06 10:31 AM, AvianResearchDivision wrote:
>>> Hi all,
>>>
>>> After running mixed models using 'lme4', I have moved on to calculating
>>> repeatabilities using the package 'rptR' on my data set.  I have 879
>>> observations over 59 individuals.  I am using the calll
>>> rpt.remlLMM(y,groups) to obtain repeatabilities, but after about 15
>> seconds
>>> I get a error stating:
>>>
>>>  R for Windows GUI front-end has stopped working
>>>
>>> A problem caused the program to stop working correctly.  Windows will
>> close
>>> the program and notify you if a solution is available.
>>>
>>>
>>> I am running Windows 7 with a i3 processor and 4 gb of memory so I
>> wouldn't
>>> expect this error to be computer performance related.
>>>
>>> I should note that I can run the rpt.aov(y,groups) call just fine.  When
>>> running the following mixed model, I don't have any convergence issues:
>>>
>>> lmer(Response~Predictor+(Predictor|Individual))
>>>
>>>
>>> Has anyone come across this issue or have any suggestions?
>>>
>>>
>>> Best,
>>> Jacob
>>>
>>
>>   (It would help to specify that rptR is available from r-forge: it took
>> me a few extra minutes to dig around and find it.)
>>
>>   For what it's worth, rpt.remlLMM appears to use nlme::lme (not
>> lme4::lmer) internally.   There doesn't seem to be anything particularly
>> scary in the guts of the function (e.g. no calls to compiled code), so I
>> really haven't much of a clue.  A reproducible example would probably be
>> helpful.  (Probably worth checking with the package maintainer as well:
>>  maintainer("rptR")).
>>
>>   Can you run the examples in ?rpt.remlLMM successfully?  What if you
>> take those examples and bump up the number of permutation/bootstrap
>> replicates?
>>
>>   Ben Bolker
>>
>>
>>
>>
>>
>