[R-sig-ME] MCMCglmm prior distributions

[Boby Mathew]

Hello Jarrod Hadfield,

Thank you so much for your help.  I have the winbugs code for estimation of
my marker effect but the problem is winbugs is too slow and cannot handle
large datasets.

my models is "y(observation) =Z%*%beta + noise"

here 'Z is the markers matrix coded 0 and 1 and beta is marker effect  I
used MCMCglmm for this model and included the marker matrix(Z) as random
(random=~idv(Z)).

I simulated some data and MCMCglmm was giving good results when the number
of markers were less than the number of observation. Does MCMCglmm can
handle this type of models?



I have attached the winbugs code here  for the reference.


model{
for(i in 1:n){
    y[i]~dnorm(mu[i],prec)
    mu[i]<- inprod(x[i,], beta[])
        }
for (j in 1: p){
    beta[j]~dnorm(0,tau[j])
    tau[j]<-1/var[j]
    var[j]~dgamma(0.1,0.1)
    }
sd~dunif(0,10)
sigma2<-sd*sd
prec<-1/sigma2

    }

Once again thanks for the help

regards,
Boby

On Mon, Oct 20, 2014 at 4:17 PM, Jarrod Hadfield <j.hadfield at ed.ac.uk>
wrote:

> Hi Boby,
>
> If you mean a common t-prior (with estimated scale) for the random effects
> then you cannot. All that you can do is place a fixed t-prior on the
> `fixed' effects.
>
> Cheers,
>
> Jarrod
>
>
>
>
>
> Quoting Boby Mathew <bobyboby at gmail.com> on Mon, 20 Oct 2014 15:52:24
> +0200:
>
>  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.
>>
>>
>
>
> --
> 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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