[R-sig-ME] MCMCglmm prior distributions

[Boby Mathew]

Dear jarrod hadfield,

How can I pace  individual variances with a t-prior for the random effects?
Could you please provide me an example?

thanks for the help.

regards,
Boby

On Mon, Oct 20, 2014 at 2:58 PM, Jarrod Hadfield <j.hadfield at ed.ac.uk>
wrote:

> Hi,
>
> This gives the b's a common variance. There is no point giving them
> individual variances unless you want to treat them as `fixed' but place a
> t-prior rather than a normal prior on each effect.
>
> Jarrod
>
>
>
>
>
> Quoting Boby Mathew <bobyboby at gmail.com> on Mon, 20 Oct 2014 14:42:02
> +0200:
>
>  Dear Jarrod Hadfield,
>>
>> Here I have attached a small code with the simulation code. I want to
>> estimate the effect of 'b' here. As you suggested I treated fixed effect
>> as
>> random and gave own variance. But I am not sure this is the right way.
>>
>> Could you please check whether the implementation is right?
>>
>> regards,
>> Boby
>>
>> mark=100; line=150
>>
>> x=round(matrix(runif(mark*line),nrow=mark))
>> b=rep(0,mark)
>> b[8]=3; b[80]=5;b[90]=5;
>>
>> noise=rnorm(line,0,sqrt(1))
>>
>>
>>
>> Line=1:line
>>
>> y = b%*%x + noise
>>
>> Z=t(x)
>>
>> library(MCMCglmm)
>>
>> data=data.frame(Phe=t(y),animal=Line)
>>
>> data$animal=as.factor(data$animal)
>>
>>
>> prior2.2 <- list(G = list(G1 = list(V = 1, n = 0.002)), R = list(V = 1, n
>> =
>> 0.002))
>>
>> mod_mcmc=MCMCglmm(Phe~1,random=~idv(Z),pr=T,data=data,
>> nitt=50000,thin=500,burnin=10000,prior=prior2.2)
>>
>> val=colMeans (mod_mcmc$Sol)
>>
>>
>>
>>
>> On Thu, Oct 16, 2014 at 5:51 PM, Jarrod Hadfield <j.hadfield at ed.ac.uk>
>> wrote:
>>
>>  Hi Boby,
>>>
>>> In short - no. I haven't tried this (or thought about it much), but you
>>> could treat each fixed effect as a single random effect with its own
>>> associated variance component. Presumably, you could then specify the
>>> prior
>>> for the variance component in a way that induces a prior t-distribution
>>> on
>>> the effect. Like the Laplace it has fatter tails than the Normal, but it
>>> lacks the peakiness and won't give some of the nice features of the
>>> LASSO.
>>>
>>> Cheers,
>>>
>>> Jarrod
>>>
>>>
>>>
>>>
>>> Quoting Boby Mathew <bobyboby at gmail.com> on Thu, 16 Oct 2014 16:06:13
>>> +0200:
>>>
>>>  Dear MCMCglmm users,
>>>
>>>>
>>>> Is it possible to use double exponential priors(Laplace) in MCMCglmm?
>>>>
>>>> Thanks for the helps.
>>>>
>>>> regards,
>>>> Boby
>>>>
>>>>
>>>> --
>>>> Dr. Boby Mathew
>>>> INRES, University of Bonn
>>>> Katzenburgweg 5
>>>> Phone: 0228732031
>>>> 53115, Bonn,Germany.
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>
>>>>
>>>>
>>>>
>>>
>>> --
>>> The University of Edinburgh is a charitable body, registered in
>>> Scotland, with registration number SC005336.
>>>
>>>
>>>
>>>
>>
>> --
>> Dr. Boby Mathew
>> INRES, University of Bonn
>> Katzenburgweg 5
>> Phone: 0228732031
>> 53115, Bonn,Germany.
>>
>>
>
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
>
>


-- 
Dr. Boby Mathew
INRES, University of Bonn
Katzenburgweg 5
Phone: 0228732031
53115, Bonn,Germany.

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