Truncated normal prior?

[KTM]

Hello,

For some reason I can't seem to define a truncated normal prior in JAGS. Apologies if this is a stupid question, but can anyone spot my mistake?

Thanks!

Simple example with a Poisson GLM. Whether I use T(,) or I(,) I get the same error when trying to define the model function:

Error: unexpected symbol in:
"
alpha ~ dnorm(0,0.001) T"

model = function() { 
  for(t in 1:T) {
    y1[t] ~ dpois(mu[t])  
    log(mu[t]) <- alpha + beta*x1[t] 
  } 

  alpha  ~ dnorm(0,0.001) T(0,1)
  beta  ~ dnorm(0,0.001)
}  

T = length(x1)

data = list("y1","x1","T")  
params = c("alpha","beta","mu") 

model.example = jags(data=data,param=params,n.chains=2,n.iter=1000,n.burnin=500,model.file=model) 

[Martyn Plummer]

This is due to a subtle difference between the BUGS and R languages.

I always put my model description in a separate file. You are representing it in the R language, but the line with the truncated normal is not a valid R expression. You can fool the R interpreter by inserting a semicolon like so

alpha ~ dnorm(0, 0.001);T(0,1)

[Tanja Proctor]

Hello Martyn,
I am having the same problem as KTM. But putting the semicolon in, does not work for me. Unfortunately the same error is produced. I wondered if I could put it as this:
alpha ~ dnorm(0, 0.001)*T(0,1)
This seems to work but I am not sure if it still means the same.

[KTM]

Thank you so much!