[R-sig-ME] Resume terminated lmer fit if verbose=TRUE?

[Dennis Murphy]

Just out of curiosity, why would you need a seven factor interaction
(assuming V1-V7 are all factors)? For that matter, why would you need
more than 2fi's? Is there some scientific reason why that might make
sense?

Dennis

On Wed, Jul 27, 2011 at 11:39 AM, Mike Lawrence <Mike.Lawrence at dal.ca> wrote:
> Thanks to Harold for pointing out the start argument and indicating
> that the verbose output can be supplied as its value. Thanks also to
> both Harold and Ben for warning on over-parameterization, though it
> may not fully apply here as my model is of the form "y ~ (1|random) +
> V1*V2*V3*V4*V5*V6*V7". (well, I might have a priori reason to
> eliminate one or two fixed effects...)
>
> Mike
>
> On Wed, Jul 27, 2011 at 10:47 AM, Ben Bolker <bbolker at gmail.com> wrote:
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>> On 07/27/2011 09:29 AM, Doran, Harold wrote:
>>> Yes. See ?lmer and the start argument. You can provide the function
>>> with starting values, which can come as the last iteration of the
>>> output from verbose. 100 hours is a ridiculous amount of computing
>>> time.
>>
>>  Oops. I was wrong (thanks).  I was thinking of lme.
>>
>>  A common theme on this list seems to be that people set up models of
>> the form
>>
>> response ~ (a lot of fixed effects) + (a lot of fixed effects|grouping)
>>
>>  The problem here is that n fixed effects  interacting with the
>> grouping variable means n*(n+1) variance-covariance parameters, which is
>> often slow to fit ... see e.g.
>> http://article.gmane.org/gmane.comp.lang.r.lme4.devel/6308 ...
>>
>>
>>>
>>> You might want to check your model and make sure it isn't
>>> overparameterized.
>>>
>>>> -----Original Message----- From:
>>>> r-sig-mixed-models-bounces at r-project.org
>>>> [mailto:r-sig-mixed-models- bounces at r-project.org] On Behalf Of
>>>> Mike Lawrence Sent: Wednesday, July 27, 2011 9:16 AM To:
>>>> r-sig-mixed-models at r-project.org Subject: [R-sig-ME] Resume
>>>> terminated lmer fit if verbose=TRUE?
>>>>
>>>> Hi folks,
>>>>
>>>> I ran a binomial lmer on a large data set with lots of levels of a
>>>> random effect (1000+) and a large fixed effects structure (7
>>>> variables all interacting). My local machine wasn't up to the task
>>>> (it needs about 16GB of memory so far as I can tell), so I put it
>>>> on a serial node on a supercomputer to which I have access. I asked
>>>> for 100 hours of compute time, but it seems that the model went
>>>> over time and the process was terminated by the system's queue.
>>>> However, I ran it in verbose mode and have all the output, so I'm
>>>> wondering if there's any way to use this information to resubmit
>>>> the job and have it resume where it left off. Any ideas?
>>>>
>>>> Cheers,
>>>>
>>>> Mike
>>>>
>>>> -- Mike Lawrence Graduate Student Department of Psychology
>>>> Dalhousie University
>>>>
>>>> Looking to arrange a meeting? Check my public calendar:
>>>> http://tr.im/mikes_public_calendar
>>>>
>>>> ~ Certainty is folly... I think. ~
>>>>
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