Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

Brief review of conditional probability and expectation followed by a study of Markov chains, both discrete and continuous time. Queuing theory, terminology, and single queue systems are studied with ...

A special structure in dynamic programming which has been studied by Bellman, Blackwell, D'Épenoux, Derman, Howard, Manne, Oliver, Wolfe and Dantzig, and others is the problem of programming over a ...

Reversible jump methods are the most commonly used Markov chain Monte Carlo tool for exploring variable dimension statistical models. Recently, however, an alternative approach based on ...