We developed an expectation–maximization (EM) algorithm to estimate the variance parameter of the prior distribution for each regression coefficient.

We show here that these MM algorithms can be reinterpreted as special instances of expectation-maximization algorithms associated with suitable sets of latent variables and propose some original ...

We compute the model using a two-stage Expectation-Maximization-type algorithm, first fixing the cross-experiment covariance structure and using efficient Bayesian hierarchical clustering to obtain a ...