[R-sig-ME] R-sig-mixed-models Digest, Vol 115, Issue 4

[Isaac Adeniyi]

Thank you very much. I believe this will go a long way to help me.<div
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On 7/4/16, r-sig-mixed-models-request at r-project.org
<r-sig-mixed-models-request at r-project.org> wrote:
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> Today's Topics:
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>    1. Help concerning GLMM estimation needed (Isaac Adeniyi)
>    2. Re: Help concerning GLMM estimation needed (Ben Bolker)
>
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> ----------------------------------------------------------------------
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> Message: 1
> Date: Sun, 3 Jul 2016 17:14:56 +0100
> From: Isaac Adeniyi <aizick.adeniyi89 at gmail.com>
> To: R-Sig-Mixed-Models at r-project.org
> Subject: [R-sig-ME] Help concerning GLMM estimation needed
> Message-ID:
> 	<CANMfBzUpg1=62MCFJFaP8N1K5+9EHfxzEHX8EXtbGkYZEJyhsw at mail.gmail.com>
> Content-Type: text/plain; charset=UTF-8
>
> Dear all,
>
> Good day all. I have used lme4 quite a lot and i must say that it is a
> wonderful work.
> I would like to use glmer with other distributions like the
> generalized poisson and com-poisson distribution. I am having hard
> time understanding how to approximate the logliklihood  and expressing
> the mathematics involved. I would love you to point me in a direction
> that will be helpful. Materials such as links to websites, papers and
> textbooks will be helpful. Also,can you give some hints on how I can
> modify the glmer codes to make it work for these distributions. Thanks
> a lot for the help.
>
>
>
> ------------------------------
>
> Message: 2
> Date: Sun, 3 Jul 2016 22:03:05 -0400
> From: Ben Bolker <bbolker at gmail.com>
> To: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] Help concerning GLMM estimation needed
> Message-ID: <5779C3D9.3000604 at gmail.com>
> Content-Type: text/plain; charset=windows-1252
>
>
>   This is going to be a bit of a challenge.  glmer really depends on
> extensions of the machinery used in GLM (see e.g. McCullagh and Nelder
> or Barnett and Dobson or ...)  *If* the distribution is in the
> exponential family, then you should be able to define a new family
> argument for it following the existing ones (binomial, Poisson, Gamma,
> etc.), which defines the mean-variance relationship.  However, many
> extensions of the exponential family (e.g. negative binomial with an
> unspecified shape parameter) won't work without additional machinery.
> (You could do what glmer.nb does, wrapping an internal loop that
> estimates an exponential family model with a fixed parameter inside an
> outer loop ...)
>
> The machinery of Laplace approximation is described e.g. in
>
> Madsen, Henrik, and Poul Thyregod. Introduction to General and
> Generalized Linear Models. CRC Press, 2011.
>
>  For mixed models using arbitrary conditional distributions, a better
> start might be the TMB or glmmTMB projects (see kaskr/adcomp and
> glmmTMB/glmmTMB on Github).  Or you could look into generalized
> estimating equation machinery, which only needs to know the
> mean-variance relationship.
>
>
> On 16-07-03 12:14 PM, Isaac Adeniyi wrote:
>> Dear all,
>>
>> Good day all. I have used lme4 quite a lot and i must say that it is a
>> wonderful work.
>> I would like to use glmer with other distributions like the
>> generalized poisson and com-poisson distribution. I am having hard
>> time understanding how to approximate the logliklihood  and expressing
>> the mathematics involved. I would love you to point me in a direction
>> that will be helpful. Materials such as links to websites, papers and
>> textbooks will be helpful. Also,can you give some hints on how I can
>> modify the glmer codes to make it work for these distributions. Thanks
>> a lot for the help.
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
>
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> End of R-sig-mixed-models Digest, Vol 115, Issue 4
> **************************************************
>