[R-sig-ME] Slight differences in fitted coefficients in lme4_1.0-6 compared to lme4_0.999999-2

[Ulf Köther]

@ Jake: I am not in any sense a statistician nor programmer and hence no
reference, but I can just support this observation. I often have noisy
data which in 90% of the cases cannot be fit using NM (non-convergence
although with many iterations) but which is consistently dealt with by
using bobyqa (with an equal amount of iterations)...
And I do not have the impression that its results seem to be inaccurate,
but that NM gets stuck in many situations.

Ulf

Am 07.02.2014 23:09, schrieb Jake Westfall:
> Not sure if this thread is the time/place for me to bring this up, but here goes... I *routinely* find that the new Nelder-Mead optimizer in lme4 >= 1.0 provides worse solutions than the old bobyqa optimizer -- "worse" in the sense that, comparing the same model fitted to the same dataset using NM vs. bobyqa, the coefficients are noticeably different and deviance for the former model is noticeably higher. When I switch to bobyqa I pretty much reproduce the results of my models fitted under lme4 < 1.0... and bobyqa is faster too! At this point, I've gotten to where I just always instruct lme4 to use bobyqa and don't even check anymore to see what Nelder-Mead comes up with. One very important thing to mention here is that the overwhelming majority of models that I fit involve crossed random effects. So maybe the new Nelder-Mead optimizer fairly consistently outperforms bobyqa for nested random effects models, and this is the motivation for making it the new lme4 default, but i!
>  n my experience, for the kind of models that I fit, bobyqa pretty much always does better.
>
> Jake
>
>> Date: Fri, 7 Feb 2014 15:51:44 -0500
>> From: bbolker at gmail.com
>> To: r-sig-mixed-models at r-project.org
>> Subject: Re: [R-sig-ME] Slight differences in fitted coefficients in lme4_1.0-6 compared to lme4_0.999999-2
>>
>> On 14-02-07 03:34 PM, Tom Wenseleers wrote:
>>> Dear all, I noticed that I get very slight differences in my current
>>> lme4 1.0-6 models compared to the old ones I obtained earlier using
>>> lme4_0.999999-2. I was just wondering whether it would somehow still
>>> be possible to reproduce the output of the old lme4_0.999999-2, by
>>> setting appropriate options of the optimizer to use etc? Or is this
>>> not possible? I also tried installing the old lme4 version using
>>> install_url in package devel, but if I try this I get a complaint
>>> that the old version doesn't work with R.0.2. Any easy way to go back
>>> to the old version (I need this to be able to fully reproduce
>>> published results)?
>>>
>>   I think you should be able to install lme4.0 from
>> http://lme4.r-forge.r-project.org/repos/  to reproduce previous outputs.
>>  You *might* be able to reproduce previous results by setting
>> control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")),
>> but I don't think we could guarantee that -- too much of the internal
>> machinery has changed too radically.
>>
>>   Ben Bolker
>>
>>
>>
>>> Cheers, Tom
>>>
>>>
>>>
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>>>
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