Abstract
A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to numerical problems arising in statistics, are discussed.
Keywords
Rejection samplingMathematicsMarkov chain Monte CarloMonte Carlo methodHybrid Monte CarloGeneralizationSlice samplingSampling (signal processing)Applied mathematicsExposition (narrative)Markov chainMonte Carlo integrationQuasi-Monte Carlo methodAlgorithmStatistical physicsStatisticsComputer scienceMathematical analysis
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Publication Info
- Year
- 1970
- Type
- article
- Volume
- 57
- Issue
- 1
- Pages
- 97-109
- Citations
- 14735
- Access
- Closed
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Cite This
W. Keith Hastings
(1970).
Monte Carlo sampling methods using Markov chains and their applications.
Biometrika
, 57
(1)
, 97-109.
https://doi.org/10.1093/biomet/57.1.97
Identifiers
- DOI
- 10.1093/biomet/57.1.97