On a multivariate implementation of the Gibbs sampler

  title={On a multivariate implementation of the Gibbs sampler},
  author={L A Garc{\'i}a-Cort{\'e}s and D Sorensen},
  journal={Genetics, Selection, Evolution : GSE},
  pages={121 - 126}
It is well established that when the parameters in a model are correlated, the rate of convergence of Gibbs chains to the appropriate stationary distributions is faster and Monte-Carlo variances of features of these distributions are lower for a given chain length, when the Gibbs sampler is implemented by blocking the correlated parameters and sampling from the respective conditional posterior distributions takes place in a multivariate rather than in a scalar fashion. This block sampling… CONTINUE READING