Skip to content
Register Sign in Wishlist

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

$ 64.99 (P)

Add to cart Add to wishlist

Other available formats:

Looking for an examination copy?

This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact providing details of the course you are teaching.

Product filter button
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 This book contains new results and previously unpublished material not available elsewhere.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    • Contains a wealth of new and previously unpublished material
    Read more

    Reviews & endorsements

    '… this book is of interest to researchers attracted by hidden Markov and semi-Markov models. It covers probabilistic and statistical treatments of the considered topics, and introduces the reader … to possible applications, mainly in genomics. Hence, Ph.D. students and specialists in the area of hidden Markov processes are invited to consider this book as a reference in their activities.' Antonio Di Crescenzo, MathSciNet

    ‘… dedicated mostly to graduate students and providing a rigorous and rather complete mathematical introduction to the theory of hidden Markov models as well as hidden semi-Markov models under main assumption that the hidden process is a finite state Markov chain. The semi-Markov models appear when the assumption that the length of time the chain spends in any state is geometrically distributed is relaxed. The authors carefully construct these processes on the canonical probability space and then derive filters and smoother, as well as the Viterbi estimates. The central role plays the EM Algorithm.’ Jerzy Ombach, ZB Math Reviews

    See more reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    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

    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

  • 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).

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×
warning icon

Turn stock notifications on?

You must be signed in to your Cambridge account to turn product stock notifications on or off.

Sign in Create a Cambridge account arrow icon

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.