Markov Chain Monte Carlo Methods

  • Kenneth Lange
Part of the Statistics for Biology and Health book series (SBH)


Mapping disease and marker loci from pedigree phenotypes is one of the most computationally onerous tasks in modern biology. Even tightly optimized software can be quickly overwhelmed by the synergistic obstructions of missing data, multiple marker loci, multiple alleles per marker locus, and inbreeding. This unhappy situation has prompted mathematical and statistical geneticists to adapt recent stochastic methods for numerical integration to the demands of pedigree analysis [9, 15, 16, 21, 25, 26, 28]. The current chapter explains in a concrete genetic setting how these powerful stochastic methods operate.


Markov Chain Markov Chain Monte Carlo Transition Rule Markov Chain Monte Carlo Method Acceptance Probability 
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 1997

Authors and Affiliations

  • Kenneth Lange
    • 1
  1. 1.Department of Biostatistics and MathematicsUniversity of MichiganAnn ArborUSA

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