Perfect Sampling

  • Christian P. Robert
  • George Casella
Part of the Springer Texts in Statistics book series (STS)


The previous chapters have dealt with methods that are quickly becoming “mainstream”. That is, analyses using Monte Carlo methods in general, and MCMC specifically, are now part of the applied statistician’s tool kit. However, these methods keep evolving, and new algorithms are constantly being developed, with some of these algorithms resulting in procedures that seem radically different from the current standards


Markov Chain Acceptance Probability Transition Kernel Slice Sampler Continuous State Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Christian P. Robert
    • 1
  • George Casella
    • 2
  1. 1.CEREMADEUniversité Paris DauphineParis Cedex 16France
  2. 2.Department of StatisticsUniversity of FloridaGainesvilleUSA

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