[R-sig-ME] Zipoisson MCMCglmm for abundance data

[Jarrod Hadfield]

No problem. I read the Science paper last night - a great paper!

Quoting Daniel Sol <dsolrueda at gmail.com> on Tue, 27 Nov 2012 15:32:21 +0100:

> Great, Jarrod. Many thanks for all your help.
>
> Cheers,
>
> Dani
>
> 2012/11/27 Jarrod Hadfield <j.hadfield at ed.ac.uk>:
>> Hi,
>>
>> Sorry forgot that one. Have,
>>
>> us(at.level(trait,1)+at.level(trait,1):dens.surr):location
>>
>> instead of
>>
>> us(at.level(trait,1)):location
>>
>> but be careful, this is a complicated model.
>>
>> Cheers,
>>
>> Jarrod
>>
>>
>>
>>
>>
>>
>> to the random model.
>>
>> Quoting Daniel Sol <dsolrueda at gmail.com> on Tue, 27 Nov 2012 15:13:29 +0100:
>>
>>> Dear Jarrod,
>>>
>>> many thanks for the rapid answer and very useful advice. Following
>>> your advice, I'm gonna use the following code.
>>>
>>> zi.prior <-  list(R = list(V = diag(2), n = 0.002, fix = 2),
>>>               G = list(G1 = list(V = 1, n = 0.002),
>>>               G2 = list(V = 1, n = 0.002),
>>>                    G3 = list(V = 1, n = 0.002),
>>>                    G4 = list(V = 1, n = 0.002)))
>>>
>>> m2 <- MCMCglmm(abund.urb ~ trait-1 + at.level(trait,1):dens.surr,
>>>                          random = ~idh(at.level(trait,1)):location      +
>>>               idh(at.level(trait,1)):animal +
>>>                                        idh(at.level(trait,1)):sp2 +
>>>                                        us(mesd):units,
>>>                                             rcov = ~ idh(trait):units,
>>>                                        prior = zi.prior,
>>>                                        pedigree=tr[[1]],
>>>                                        data = dat0.phyl, family =
>>> "zipoisson", verbose = TRUE,
>>>                                        pr = FALSE, pl = FALSE)
>>>
>>> However, I'm still wondering how to run the same model allowing the
>>> relationship between abundance in the city (abund.urb) and density in
>>> the surrounding habitats (dens.surr) to vary across locations
>>> (location) in both intercepts and slopes.
>>>
>>> Many thanks again,
>>>
>>> Dani
>>>
>>>
>>> 2012/11/27 Jarrod Hadfield <j.hadfield at ed.ac.uk>:
>>>>
>>>> 1/3b You need to drop at.level(trait,1):location from the fixed model as
>>>> you
>>>> have it in the random part of the model (although this may just be a
>>>> typo).
>>>> I would also have trait-1 as you do not want the intercept for the
>>>> Poisson
>>>> process and the zero-inflation to be the same.
>>>>
>>>> 2. If you have many observations per species then I would put a
>>>> non-phylogenetic species effect in too. If there are few (at the limit,
>>>> only
>>>> one) then it may be hard to separate the phylogenetic from the
>>>> non-phylogenetic.
>>>>
>>>> 3a. this looks fine but make sure to put mesd in dat0.phyl (I presume
>>>> this
>>>> is the case otherwise MCMcglmm should spit an error, if it did not please
>>>> tell me). Not sure how effort is measured, but you may not expect a
>>>> linear
>>>> relationship between 1/(effort) and the measurement error variance of the
>>>> counts on the log scale. (I presume ** should be ^ in your code)
>>>>
>>>> 4. With  the 2x2 "idh" structure on the residuals I would use nu=0.002
>>>> rather than nu=1.002. Only with a 2x2 "us" structure
>>>> is the degree of belief for the marginal distribution of a single
>>>> variance
>>>> 0.002 when specifying nu=1.002. Parameter expanded priors might also be
>>>> entertained for the random effect variances. They will also improve
>>>> mixing
>>>> if the varinaces are close to zero.
>>>
>>>
>>>
>>>
>>> --
>>> Daniel Sol
>>> CREAF (Centre for Ecological Research and Applied Forestries)
>>> CSIC (Centre for Advanced Studies of Blanes-Spanish National Research
>>> Council)
>>> Autonomous University of Barcelona, Bellaterra, Catalonia E-08193, Spain
>>> TEL: +34 93-5814678
>>> FAX: +34 93-5814151
>>> E-MAIL: d.sol at creaf.uab.es
>>>
>>>
>>
>>
>>
>> --
>> The University of Edinburgh is a charitable body, registered in
>> Scotland, with registration number SC005336.
>>
>>
>
>
>
> --
> Daniel Sol
> CREAF (Centre for Ecological Research and Applied Forestries)
> CSIC (Centre for Advanced Studies of Blanes-Spanish National  
> Research Council)
> Autonomous University of Barcelona, Bellaterra, Catalonia E-08193, Spain
> TEL: +34 93-5814678
> FAX: +34 93-5814151
> E-MAIL: d.sol at creaf.uab.es
>
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>
>



-- 
The University of Edinburgh is a charitable body, registered in
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