Monte Carlo Sampling Methods Using Markov Chains and Their Applications

  title={Monte Carlo Sampling Methods Using Markov Chains and Their Applications},
  author={W. K. Hastings},
SUMMARY 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. For numerical problems in a large number of dimensions, Monte… Expand
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  • J. Spall
  • Mathematics
  • Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301)
  • 2002
Markov chain Monte Carlo (MCMC) is a powerful means for generating random samples that can be used in computing statistical estimates, numerical integrals, and marginal and joint probabilities. TheExpand
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  • Computer Science, Mathematics
  • 2018
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A generating function for averages over the orthogonal group
  • A. T. James
  • Mathematics
  • Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences
  • 1955
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