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Introduction to Hidden Semi-Markov Models

$64.99 (P)

Part of London Mathematical Society Lecture Note Series

  • Date Published: May 2018
  • availability: In stock
  • format: Paperback
  • isbn: 9781108441988

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About the Authors
  • Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state framework suitable for senior undergraduates and graduates. The authors then introduce semi-Markov chains and hidden semi-Markov chains, before developing related estimation and filtering results. Genomics applications are modelled by discrete observations of these hidden semi-Markov chains. This book contains new results and previously unpublished material not available elsewhere. The approach is rigorous and focused on applications.

    • Presents the theory in a discrete time, finite state framework
    • Readily accessible to senior undergraduate and first-year graduate students
    • Contains a wealth of new and previously unpublished material
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    Product details

    • Date Published: May 2018
    • format: Paperback
    • isbn: 9781108441988
    • length: 184 pages
    • dimensions: 227 x 151 x 11 mm
    • weight: 0.29kg
    • availability: In stock
  • Table of Contents

    Preface
    1. Observed Markov chains
    2. Estimation of an observed Markov chain
    3. Hidden Markov models
    4. Filters and smoothers
    5. The Viterbi algorithm
    6. The EM algorithm
    7. A new Markov chain model
    8. Semi-Markov models
    9. Hidden semi-Markov models
    10. Filters for hidden semi-Markov models
    Appendix A. Higher order chains
    Appendix B. An example of a second order chain
    Appendix C. A conditional Bayes theorem
    Appendix D. On conditional expectations
    Appendix E. Some molecular biology
    Appendix F. Earlier applications of hidden Markov chain models
    References
    Index.

  • Authors

    John van der Hoek, University of South Australia
    John van der Hoek is an Associate Professor at the University of South Australia. He has authored papers in partial differential equations, free boundary value problems, numerical analysis, stochastic analysis, actuarial science and mathematical finance. With Robert Elliott he co-authored Binomial Methods in Finance.

    Robert J. Elliott, University of Calgary
    Robert J. Elliott is a Research Professor at the University of South Australia. Previously he held positions at universities around the world, including Yale, Oxford, Alberta, Calgary and Adelaide. He has authored nine books, including Mathematics of Financial Markets (2004, with P. E. Kopp) and Stochastic Calculus and Application (1982).

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