Hi,
I am trying to replicate in JAGS on my own data the OPEN BUGS code for a Pagel’s lambda model (you can find it here: http://link.springer.com/content/esm/art:10.1186/1471-2148-12-102/file/MediaObjects/12862_2012_2257_MOESM1_ESM.pdf) in the supple. materials of this paper: http://link.springer.com/article/10.1186%2F1471-2148-12-102
My model looks like this:
bovids.jg<-function(){
#Linear regression and multivariate normal likelihood
for (i in 1:Nspec) {
mu[i] <- alpha+beta*GS[i]
}
Lf[1:Nspec]~dmnorm(mu[],TAU[,])
#Priors
alpha ~ dnorm(0,1.0E-06)
beta ~ dnorm(0,1.0E-06)
lambda ~ dunif(0,1)
tau ~ dgamma(1,1)
sigma <- 1/sqrt(tau)
#Tree sampling and lambda computation
for (k in 1:Ntree) {
p[k] <- 1/Ntree
}
K~dcat(p[])
#LAMBDA is a matrix with off-diagonal lambda value and 1 in the diagonal
Mlam <- lambda*multiVCV[,,K]+(1-lambda)*ID
TAU <- tau*inverse(Mlam)
}
It works fine, as long I do not have missing values in the dependent variable (Lf). In which case I get the following error message:
Error in jags.model(model.file, data = data, inits = init.values, n.chains = n.chains, :
RUNTIME ERROR:
Compilation error on line 6.
Lf[1:97] has missing values
Should JAGS not take care on his own of the missing values?
Thanks a lot to anybody can help me!
best regards,
Achaz von Hardenberg
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