Solved – WinBUGS truncated normal distribution

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I am estimating a stochastic frontier with a mixed model.
So far the half normal distribution worked good but I need a truncated normal distribution. It does not work, and I receive the error „Expected collection operator c“. I am using R2WinBUGS and as you can see in the model I have tried OpenBUGS and WinBUGS. Any suggestion?
My model looks like:

for (i in 1:N)  {      mu[i] <- alpha + x[i,1]*beta[1] + x[i,2]*beta[2] + x[i,3]*beta[3] +           x[i,4]*beta[4] + x[i,5]*beta[5] + u0[county[i]] + u1[county[i]]*x[i,1] +           u2[county[i]]*x[i,2] + u3[county[i]]*x[i,3] + u4[county[i]]*x[i,4] +           u5[county[i]]*x[i,5] - z[ID[i]]      y[i] ~ dnorm(mu[i], tau)  }   for (i in 1:220) {     z[i] ~ djl.dnorm.trunc(rho,lambda,0,1000)      z[i] ~ dnorm(rho,lambda)T(0,100)  #For openbugs      eff[i] <- exp(-z[i]) }

prior for rho~dnorm(0,0.027)

I would appreciate your help!
Regards,
Daniel

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Best Answer

For truncating, I use the operator I i.e.:

x ~ dnorm(mean, tau)I(low, high)

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