Work

Bayesian Computational Tools

Year: 2013

Type: review

Abstract: This article surveys advances in the field of Bayesian computation over the past 20 years from a purely personal viewpoint, hence containing some ommissions given the spectrum of the field. Monte Carlo, MCMC, and ABC themes are covered here, whereas the rapidly expanding area of particle methods is only briefly mentioned and different approximative techniques such as variational Bayes and linear Bayes methods do not appear at all. This article also contains some novel computational entries on the double-exponential model that may be of interest.

Source: Annual Review of Statistics and Its Application

DOI: 10.1146/annurev-statistics-022513-115543

Author: Christian P. Robert

Institutions: Centre de Recherche en Mathématiques de la Décision, Université Paris Dauphine-PSL

Language: English

Topic: Markov Chains and Monte Carlo Methods

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

Funder: Agence Nationale de la Recherche

Award: Statistical Calibration