Markov chain Monte Carlo methods
Markov chain Monte Carlo methods
This chapter provides a brief summary of Markov chain Monte Carlo (MCMC) methods. The chapter is organized as follows. Section 6.2 describes the Metropolis–Hastings algorithm and its generalized version. Section 6.3 considers the Gibbs sampling algorithm while additional topics of importance, such as sampling with latent data and calculation of the marginal likelihood, are discussed in Section 6.4. Section 6.5 has concluding remarks.
Keywords: MCMC methods, Metropolis–Hastings algorithm, Gibbs sampling algorithm, latent data, marginal likelihood
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