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Sampling-Based Approaches to Calculating Marginal Densities
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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Andrieu, C., de Freitas, N., Doucet, A., & Jordan, M. I. (2003) · Machine Learning · doi:10.1023/a:1020281327116 · Cited by 2,451
Using simulation methods for bayesian econometric models: inference, development,and communication
Geweke, J. (1999) · Econometric Reviews · doi:10.1080/07474939908800428 · Cited by 958
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Roberts, G. O., & Rosenthal, J. S. (2004) · Probability Surveys · doi:10.1214/154957804100000024 · Cited by 734
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Martin, A. D., Quinn, K. M., & Park, J. H. (2011) · Journal of Statistical Software · doi:10.18637/jss.v042.i09 · Cited by 608
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
Xiong, L., Chen, X., Huang, T.-K., Schneider, J., & Carbonell, J. G. (2010) · Proceedings of the 2010 SIAM International Conference on Data Mining · doi:10.1137/1.9781611972801.19 · Cited by 585
Metadata
- Authors
- Gelfand, A. E., & Smith, A. F. M.
- Venue
- Journal of the American Statistical Association
- Published
- 1990-06-01
- Volume
- 85
- Issue
- 410
- Pages
- 398-398
- ISSN
- 0162-1459 (ISSN-L)
- OpenAlex
- W4302434451
- Cited by
- 1,504
- References
- 0
- FWCI
- 14.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Sampling-Based Approaches to Calculating Marginal Densities. https://app.cochat.ai/papers/10.2307/2289776
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- Gelfand, A. E., & Smith, A. F. M. (1990). Sampling-Based Approaches to Calculating Marginal Densities. Journal of the American Statistical Association. https://doi.org/10.2307/2289776
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
