Sampling-based approaches to calculating marginal densities

Published

Journal Article

Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions. The three approaches will be reviewed, compared, and contrasted in relation to various joint probability structures frequently encountered in applications. In particular, the relevance of the approaches to calculating Bayesian posterior densities for a variety of structured models will be discussed and illustrated. © 1990 Taylor & Francis Group, LLC.

Full Text

Duke Authors

Cited Authors

  • Gelfand, AE; Smith, AFM

Published Date

  • January 1, 1990

Published In

Volume / Issue

  • 85 / 410

Start / End Page

  • 398 - 409

Electronic International Standard Serial Number (EISSN)

  • 1537-274X

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1080/01621459.1990.10476213

Citation Source

  • Scopus