Hi all,
I am trying to implement the WinBUGS spatial conditional autoregression model
on page 11.11 of Applied Spatial Data Analysis in R. I have about 3300 polygons
with about 17,000 adjacencies in the set.
I have changed the model only by removing the beta term as, for now, I don't
have any variables to include - I want simply to do a spatially smoothed model
with no covariates.
Anyhow the code runs fine under R - but I am constantly getting a Trap Error in
Winbugs - Index out of range.
My BUGs code looks like this:
model
{
for(i in 1:N)
{
observed[i]~dpois(mu[i])
log(theta[i])<-alpha + u[i] + v[i]
mu[i]<-expected[i]*theta[i]
u[i] ~dnorm(0,precu)
}
v[1:N]~car.normal(adj[],weights[],num[],precv)
alpha ~dflat()
precu ~dgamma (0.001, 0.001)
precv ~dgamma (0.001, 0.001)
}
and my R code like this - (I've deliberately kept the iterations low in trying
to figure out the problem but I get the error even within 1000 iterations).
nb<-poly2nb(EDdata2,queen=T)
nb.w<-nb2listw(nb,zero.policy=T,style="B")
nbBugs<-listw2WB(nb.w)
BugsDir<-"C:/Program Files/WinBUGS14/"
N<-length(EDdata2$nm_tt_c)
d<-list(N = N, observed =EDdata2$nm_tt_c, expected = EDdata2$tot_exp,
adj=nbBugs$adj, weights=nbBugs$weights, num=nbBugs$num)
inits<-list(list(u=rep(0,N),v=rep(0,N),alpha=0,precu=0.001,precv=0.001))
MCMCres<-bugs(data=d,inits=inits,bugs.directory=BugsDir,parameters.to.save=c("theta","alpha"),n.chains=1,n.iter=1000,n.burnin=500,n.thin=1,
model.file="ALS_spatial_CAR.txt")
I don't know if WinBUGS falls under the remit here ?? But was hoping someone
might have some idea whats causing my TRAP errors as I am at a loss.
Many thanks all,
James
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