Bayesian Statistics in Action by Raffaele Argiento Ettore Lanzarone Isadora Antoniano Villalobos & Alessandra Mattei

Author:Raffaele Argiento, Ettore Lanzarone, Isadora Antoniano Villalobos & Alessandra Mattei
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

2.2 Metropolis Algorithm

Here we embed the DTQ method’s likelihood computation into a Metropolis algorithm to sample from the posterior. In the Metropolis algorithm, we construct an auxiliary Markov chain which is designed to have an invariant distribution given by the posterior . This Markov chain is constructed as , where is a random vector with dimension equal to that of the parameter vector . In this paper, we choose all components of to be independent normal random variables with known means and variances.

The Metropolis algorithm is as follows:Choose value for .

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.