Hi all, I'm trying to write a code that performs the Metropolis-within-Gibbs algorithm, to draw values of a 2x1 parameter vector from a posterior distribution that doesn't have a well known form. So one of the parameters, theta1, has a well known full conditional distribution( for which the gibbs sampler can be used), but the other, theta2, doesn't have a well known full conditional (for which a random walk Metropolis-Hastings algorithm should be used). But theta1 depends on the generated value of theta 2. I know this code can be hand-written, but is there any package that can perform such update of the Metropolis-within-gibbs algorithm and provide me with acceptance rates or different scaling for the proposal distribution? I've checked the gibbs.met package but it used an independent proposal distribution. I went through the MCMCpack but couldn't find a function that performs what I want. So is there any other packages that you recommend or do I have to write my own functions? Thanks for helping, Maram Salem [[alternative HTML version deleted]]