model{
for (i in 1:n) {
      z[i] <- log(y[i]) 
      z[i] ~ dnorm(mu[i], tau)
      mu[i] <- beta[1]*Ind[i,1]+beta[2]*Ind[i,2]+beta[3]*Ind[i,3]+beta[4]*Ind[i,4] }
      
      tau ~ dgamma(0.01,0.01)
      sigma <- 1 / sqrt(tau)
      beta[1] ~ dnorm(0, 0.001)
      beta[2] ~ dnorm(0, 0.001)
      beta[3] ~ dnorm(0, 0.001)
      beta[4] ~ dnorm(0, 0.001)

 	becb < - exp(beta[1])
     becff <- exp(beta[1]+beta[4])
     ccb  <- exp(beta[2])
     ccff <- exp(beta[2]+beta[4])
     gcb <- exp(beta[3])
     gcff <- exp(beta[3]+beta[4])    

}