[R-sig-ME] nlmer and the binomial distribution.

[Kenneth Knoblauch]

Just a point of note, that the repeated package is on CRAN

https://cran.r-project.org/web/packages/repeated/index.html

and the gnm package on CRAN might be able to handle this, too,

https://cran.r-project.org/web/packages/gnm/index.html

Good luck.

> nlmer does *not* handle non-Gaussian (exponential family) models
> (GNLMMs). I don't know of a mainstream, out-of-the-box solution for
> frequentist fits of GNLMMs in R.
> 
> * brms can handle nonlinear models with non-Gaussian responses
> <https://cran.r-project.org/web/packages/brms/vignettes/brms_nonlinear.html>
> . It does Bayesian estimation only, but optimization *could* be hacked
> if you wanted <https://github.com/paul-buerkner/brms/issues/115>
> 
> * you could try the gnlmm function in Jim Lindsey's repeated package;
> you'll have to install it and the rmutils package from source 
> available
> at <http://www.commanster.eu/rcode.html>

> * to my knowledge the TMB package would be the most
> straightforward/modern way to fit GNLMMs in R, but you would have to
> figure out how to write the TMB code.
> 
> On 2019-02-10 4:50 a.m., Rolf Turner wrote:
>> 
>> It is not clear to me from the help file whether the nlmer() function
>> from the lme4 package can be used to fit non-linear mixed models when
>> the response has a discrete distribution, in particular a binomial
>> distribution. I'd like to fit a mixed binomial model in which the
>> success probability *cannot* be expressed as "linkinv(linear 
>> predictor)"
>> where "linkinv()" is the inverse of one of the "standard" link 
>> functions
>> (logit, probit, or cloglog) and the linear predictor is linear in the
>> model parameters, but has to be expressed as a more complicated
>> non-linear function of the parameters and the predictors.
>> 
>> If it is possible, how should the response appear in the formula? 
>> Should
>> it be given in the form
>> 
>> cbind(successes,failures) ~ ... ?
>> 
>> And how should the non-linear function be structured so as to
>> accommodate the two-column nature of the response?
>> 
>> I *might* be able to figure all this out by experimenting, but the 
>> range
>> of possible wrong approaches and wrong garden paths down which to 
>> lead
>> myself kind of overwhelms me.
>> 
>> So I thought I'd ask here and maybe save myself a bit of time. :-)
> 
>> cheers,
> v
>> Rolf Turner
>> 
>> P. S. It's quite possible that my question makes no real sense at 
>> all.
>> If so, please feel free to tell me so, but a bit of elaboration as to
>> why would be appreciated.
>> 
>> R. T.
>> 


-- 
Kenneth Knoblauch
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