Sampling-Based Approaches to Calculating Marginal Densities

1990/06/01 by Alan E. Gelfand, A. F. M. Smith · 6 citations
Decision Sciences · Mathematics · Agricultural and Biological Sciences · #demographic modeling and climate adaptation #Census and Population Estimation #Rural development and sustainability

paper · doi:10.2307/2289776

openalex publication_date 1990/06/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

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.

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• 1990 in science [wikipedia]