[R-sig-ME] Why do lme() models runs so fast and converge as compared to lmer()?
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Mon Sep 18 02:11:40 CEST 2023
This is mildly surprising but not impossible. I haven't looked into
it/run any experiments yet, but:
* lme handles a more restricted range of model types, so it's possible
that its algorithm is faster on simple examples;
* 'doesn't converge' may not be the issue you think it is. I would
improve performance and turn off convergence checking that is known to
be dodgy for large data sets via control = lmerControl(calc.derivs =
FALSE)), and more generally try these suggestions:
https://rdrr.io/cran/lme4/f/vignettes/lmerperf.Rmd
cheers
Ben Bolker
On 2023-09-17 5:21 a.m., Santosh Srinivas wrote:
> Hi, I am running the following similar models using lme() and lmer():
>
> f = y ~ x + year * post_event + (year|user_id)
>
> where,
>
> * year (integer) ranges from 0 (for the year 2010) to 10 (for the year2020);
> * post_event (factor variable) is 1 for years 2013 onwards, and 0 otherwise;
> * Number of Observations: 3586633; and
> * Number of Groups: 1109.
>
> The lme4's lmer() runs for several minutes and never succeeds to converge with any optimizer I try, whereas the former seems to converge in a few minutes.
>
> Not sure if I am doing anything wrong, or whether such convergence and performances are generally expected of lme().
>
> Request your help.
>
> Thanks & regards,
> sbs
>
>
>
>
> [[alternative HTML version deleted]]
>
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--
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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