Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject, developing the theory of Markov and semi-Markov processes in an elementary discrete time, finite state framework suitable for senior undergraduates and graduates.
Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject, developing the theory of Markov and semi-Markov processes in an elementary discrete time, finite state framework suitable for senior undergraduates and graduates.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
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.
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.
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