data{ int N; real y[N]; real x[N]; real sigma_x; } parameters{ real alpha; real beta; real xraw[N]; real sigma_y; } model{ real mu[N]; for(i in 1:N){ //mu[i] = alpha + (x[i]-xraw[i])*beta; mu[i] = alpha + xraw[i]*beta; // suppose xraw is the true value of x } for(i in 1:N){ y[i] ~ normal(mu[i], sigma_y); //xraw[i] ~ normal(0, sigma_x); xraw[i] ~ normal(x[i], sigma_x); } //alpha ~ normal(0, 10); //beta ~ normal(0, 10); //sigma_y ~ normal(0,3); non-informative priors. }