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Monte Carlo sampling methods using Markov chains and their applications

W. Keith Hastings · Biometrika · 1970

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Author / responsible party
W. Keith Hastings
Publisher
Biometrika
Year
1970
Language
English

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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.

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APA 7

Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. https://doi.org/10.1093/biomet/57.1.97

MLA

Hastings, W. Keith. "Monte Carlo sampling methods using Markov chains and their applications." 1970. https://doi.org/10.1093/biomet/57.1.97.

Chicago

Hastings, W. Keith. 1970. "Monte Carlo sampling methods using Markov chains and their applications.". https://doi.org/10.1093/biomet/57.1.97.

Harvard

Hastings, W. K. 1970, Monte Carlo sampling methods using Markov chains and their applications, Biometrika, available at: https://doi.org/10.1093/biomet/57.1.97 [Accessed 8 Aug. 2026].

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Resource details

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Title
Monte Carlo sampling methods using Markov chains and their applications
Author / contributors
W. Keith Hastings
Publisher
Biometrika
Publication year
1970
Language
English

Subjects

Explore related resources through these subjects.

Rejection sampling; Mathematics; Markov chain Monte Carlo; Monte Carlo method; Hybrid Monte Carlo; Generalization; Slice sampling; Sampling (signal processing); Applied mathematics; Exposition (narrative); Markov chain; Monte Carlo integration
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