Continuous-Time Markov Chains

An Applications-Oriented Approach

  • William J. Anderson

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xii
  2. William J. Anderson
    Pages 1-60
  3. William J. Anderson
    Pages 61-91
  4. William J. Anderson
    Pages 92-119
  5. William J. Anderson
    Pages 120-154
  6. William J. Anderson
    Pages 155-203
  7. William J. Anderson
    Pages 204-232
  8. William J. Anderson
    Pages 233-260
  9. William J. Anderson
    Pages 261-291
  10. William J. Anderson
    Pages 292-332
  11. Back Matter
    Pages 333-355

About this book


Continuous time parameter Markov chains have been useful for modeling various random phenomena occurring in queueing theory, genetics, demography, epidemiology, and competing populations. This is the first book about those aspects of the theory of continuous time Markov chains which are useful in applications to such areas. It studies continuous time Markov chains through the transition function and corresponding q-matrix, rather than sample paths. An extensive discussion of birth and death processes, including the Stieltjes moment problem, and the Karlin-McGregor method of solution of the birth and death processes and multidimensional population processes is included, and there is an extensive bibliography. Virtually all of this material is appearing in book form for the first time.


Branching process Markov chain Moment Parameter Transition function continuous-time Markov chain ergodicity hitting time probability queueing theory

Authors and affiliations

  • William J. Anderson
    • 1
  1. 1.Department of Mathematics and StatisticsMcGill UniversityMontrealCanada

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York 1991
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-7772-9
  • Online ISBN 978-1-4612-3038-0
  • Series Print ISSN 0172-7397
  • Buy this book on publisher's site
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