April 2015
Intermediate to advanced
1062 pages
40h 35m
English
This chapter deals with basic concepts and definitions concerning Monte Carlo sampling techniques. Rejection sampling and importance sampling are first introduced. Markov chains and some of their basic properties are discussed. Then the Metropolis-Hastings and Gibbs algorithms are presented. At the end of the chapter, a case study concerning change point detection is considered.
Keywords
Monte Carlo methods
Rejection sampling
Importance sampling
Markov chains
Metropolis-Hastings algorithm
Gibbs sampling
Change point detection