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R-USERS-L  2018

R-USERS-L 2018

Subject:

Re: GLMM & zero-inflated count data

From:

Ben Bolker <[log in to unmask]>

Reply-To:

UF R Users List <[log in to unmask]>

Date:

Mon, 23 Jul 2018 15:35:02 -0400

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (78 lines)

https://urldefense.proofpoint.com/v2/url?u=https-3A__bbolker.github.io_mixedmodels-2Dmisc_glmmFAQ.html-23zero-2Dinflation&d=DwIDaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=QWxQId63qB2iSP1ggUL7kQsdfEWUTu6qCGEw8Xuo91A&m=hT6cbmF3uxPVnGP_Z0x6Rv-nMcE8kqzdAJCSr7tT6mk&s=rX2BOdE5QqOUEhbGKZ_OPP_nteiPLvS5LChWOQGCyE4&e=

  suggests brms, MCMCglmm, glmmTMB as well, among others.  I would
recommend one of these two (glmmTMB if you want the easiest/fastest
frequentist approach, brms or MCMCglmm if you want to go Bayesian).
Unless you want to follow Denis Valle's advice and use a toolbox
(NIMBLE, JAGS, Stan, TMB, greta?, ...) for more power and flexibility.

  I'm getting a bit lazy about maintaining glmmADMB since glmmTMB is
essentially better in every way at this point (people should let us know
at https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_glmmTMB_glmmTMB_issues&d=DwIDaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=QWxQId63qB2iSP1ggUL7kQsdfEWUTu6qCGEw8Xuo91A&m=hT6cbmF3uxPVnGP_Z0x6Rv-nMcE8kqzdAJCSr7tT6mk&s=5RcBdvFpT9wb2C3HcsgGSLhbQCl2BrFeiSKAAjCpwOo&e= if there's something they
can do with glmmADMB that they can't (yet) with glmmTMB ... the only
thing I can think of is Gauss-Hermite quadrature).

  If you still want glmmADMB:  did you try the installation instructions
at https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_bbolker_glmmadmb&d=DwIDaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=QWxQId63qB2iSP1ggUL7kQsdfEWUTu6qCGEw8Xuo91A&m=hT6cbmF3uxPVnGP_Z0x6Rv-nMcE8kqzdAJCSr7tT6mk&s=9vzVXJtfcwZkpbJrMEse03lrQhCTEFEkV0UDIMKxhbA&e= ? If so, can you give details of
what didn't work?

  cheers
    Ben Bolker


On 2018-07-23 03:26 PM, Valle,Denis R wrote:
> Hi Fezile, the other option is to use JAGS if you are willing to go
> the Bayesian way.
> 
> This is a bit more involved but you might find the added flexibility
> useful for this (and future) modeling problems.
> 
> Best, Denis
> 
> -----Original Message----- From: UF R Users List
> [mailto:[log in to unmask]] On Behalf Of Mtsetfwa,Fezile P Sent:
> Monday, July 23, 2018 2:51 PM To: [log in to unmask] Subject:
> GLMM & zero-inflated count data
> 
> Hi all,
> 
> 
> 
> I am trying to run glmms for zero-inflated count data using the
> package glmmADMB but I can't even get the program to download.
> 
> 
> 
> I have tried install.packages, devtools and other ways, nothing. Has
> anyone used this package? Any suggestions?
> 
> 
> 
> Are there any other packages I can use for zero inflated data that
> can support a negative binomial distribution?
> 
> 
> 
> Thanks!
> 
> 
> 
> This list strives to be beginner friendly.  However, we still ask
> that you
> 
> PLEASE do read the posting guide
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.R-2Dproject.org_posting-2Dguide.html&d=DwIGaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=zAVYZd3B5rRMa_OS6MyRQQ&m=75zDimpku0VGvJSKQ9C_jtIOzsCJnYF_mxDwNMPSeLw&s=qRdTVObad76MOkgoHa6IPlKEzwrNXHBl1JnTPJoxwbQ&e=
>
>  and provide commented, minimal, self-contained, reproducible code.
> 
> This list strives to be beginner friendly.  However, we still ask
> that you PLEASE do read the posting guide
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.R-2Dproject.org_posting-2Dguide.html&d=DwIDaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=3MJaagrtDUL79e1ACXZji8lYXjs07_ujkEIg1it6gQ0&m=eeCh1Dq5BrMl7rRJ17C2UvHUCR2SmyYG9TyHjXF5fMw&s=Ofy6lMSkuMSGmApx1wOKPoRtg7PnnMa2Bwtsa_AdMEM&e=
>
> 
and provide commented, minimal, self-contained, reproducible code.
> 

This list strives to be beginner friendly.  However, we still ask that you
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

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