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November 1, 2000Technometrics5,610 citations

Monte Carlo Statistical Methods

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HKHoon KimCRChristian P. RobertGCGeorge Casella

Key Points

  • To consolidate insights on Monte Carlo statistical methods and identify contributions from various authors and groups.
  • Review of contributions from the French working group 'MC Cube' on convergence diagnostics.
  • Utilization of data and graphs provided by known statisticians for illustrative purposes.
  • Discussion of collaborative works related to Bayesian methods and convergence.
  • Identification of typographical discrepancies in the French version as noted by Douc.
  • Acknowledgment of shared resources and collaborations that enhance the understanding of Monte Carlo methods.
  • Insights drawn from various examples throughout the chapter illustratingMonte Carlo applications.

Abstract

Douc pointed out typos and mistakes in the French version, but should not be held responsible for those remaining!Part of Chapter 8 has a lot of common with a "reviewww" written by Christian Robert with Chantal Guihenneuc-Jouyaux and Kerrie Mengersen for the Valencia Bayesian meeting (and the Internet!).The input of the French working group "MC Cube," whose focus is on convergence diagnostics, can also be felt in several places of this book.Wally Gilks and David Spiegelhalter granted us permission to use their graph (Figure 2.3.1) and examples as Problems 7.44-7.55,for which we are grateful.Agostino Nobile kindly provided the data on which Figures 7.3.2and 7.3.2are based.Finally, Arnoldo Frigessi (from Roma) made the daring move of teaching (in English) from the French version in Olso, Norway

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Cite This Study

Kim et al. (2000) studied this question.

synapsesocial.com/papers/69d74144ef4aa71f97f30a15https://doi.org/10.2307/1270959
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