model {            
            for (i in 1:N2) {
                    y[i] ~ dnorm(mean[i],tau.y)        
                    mean[i]<-b0+b1*x1[i]+b2*x2[i]+b3*x3[i]                    
            } 
            tau.y<-pow(sigma.y,-2)
            sigma.y~dunif(.00001,100)
            b0 ~ dnorm(0,.01)
            b1 ~ dnorm(0,.01)
            b2 ~ dnorm(0,.01)
            b3 ~ dnorm(0,.01)
            
        }