In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussi

Included in this distribution is matlab code to generate posterior samples for linear Gaussian and binary matrix factorization (noisy-or) Indian Buffet Process models. Three different posterior sampling algorithms are provided: Gibbs, reversibl

As the computer hardware developing and the fast advances of computers in the last several years, Monte Carlo particle filter algorithms, which origin Monte Carlo methods, have become popular again. The Monte Carlo particle filter algorithms in thi