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Monte Carlo Sampling Methods Using Markov Chains and Their Applications
W. K. Hastings
Vol. 57, No. 1 (Apr., 1970), pp. 97-109
Stable URL: http://www.jstor.org/stable/2334940
Page Count: 13
You can always find the topics here!Topics: Markov chains, Matrices, Sampling distributions, Estimation methods, Metropolitan areas, Error rates, Simulations, Standard deviation, Monte Carlo methods, Statistical mechanics
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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.
Biometrika © 1970 Biometrika Trust