Christophe & Michael,
I know I didn't provide much context to my question hence it might seem weird.
But here is an example: I am trying to predict my response variable,
in a longitudinal set up,
y.pred[i] <- exp(b[1] + b[2]*treat[i] + W.pred[subject[i]] + U.pred[i])
where W.pred and U.pred are predicted values. Also we are assuming
that U.pred follows a mixture of uniforms.
I would have loved to provide the whole code and include data but I am
restricted in that sense. So I merely picked out the relevant parts.
Thanks for responding.
Regards,
Raphael
On Wed, Sep 26, 2012 at 8:18 AM, Christophe Saint-Jean
<[log in to unmask]> wrote:
> Hi Raphael,
>
> Some weird question : Are you sure that a mixture of uniform is
> identifiable (in the sense defined in the book "Finite Mixture Models") ?
>
> Best,
> Christophe.
>
>
>
> Le 26 sept. 2012 à 12:02, Raphael Fraser a écrit :
>
> Hi,
>
> My goal is to sample from a mixture of uniforms but unless U[j] is observed
> or u[j] is a number my code will not work. Is there an alternative? Can
> anyone help?
>
> Thanks,
> Raphael
>
> model {
>
> for (j in 1:M) {
>
> U[j] ~ dunif(-u[j],u[j])
> K[j] ~ dcat(p[1:N])
> u[j] <- r[K[j]]
>
> for (i in 1:N) {
> SC[j,i] <- equals(i,K[j])
> }
> }
>
> for (i in 1:N) {
> sumSC[i] <- sum(SC[,i])
> cl[i] <- step(sumSC[i] - 1)
> }
>
> NC <- sum(cl[])
>
> # Contructive DPP
> for (k in 1:N) { r[k] ~ dgamma(1.5,tau.e) }
> for (k in 1:(N-1)) { V[k] ~ dbeta(1,1) }
> for (k in 2:N) { p[k] <- V[k]*(1-V[k-1])*p[k-1]/V[k-1] }
> V[N] <- 1
> p[1] <- V[1]
>
> # priors
> tau.e <- pow(2*pow(sig.e,2),-1)
> sig.e ~ dunif(0,6)
>
> }
>
> #### INITS
> list(sig.e=3.0)
>
> #### DATA
> list(M=10,N=5)
>
> ------------------------------------------------------------------- This
> list is for discussion of modelling issues and the BUGS software. For help
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>
> --------------------------------------------
> Christophe Saint-Jean
> Lab. MIA, Dép. Informatique
> Université de La Rochelle
> http://perso.univ-lr.fr/csaintje/
> --------------------------------------------
>
>
>
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