Description

Book Synopsis
This third edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organizing it into a more teachable format. With more in-depth coverage of Markov chains and simple Markov process, the authors provide added emphasis to statistical inference in stochastic processes.

Trade Review
"…provides excellent coverage of the basic topics…Bhat and Miller have provided an excellent text and reference book.” (Interfaces, July/ August 2004)

"...an extended and well-written introduction to the theory...of stochastic processes and their applications..." (Zentralblatt Math, Vol. 1024, 2004)

"...besides conveying the concepts of stochastic processes, this book succeeds in providing insight into the reasons why for a particular topic certain lines of investigation are pursued and why certain variables/functions are introduced." (Technometrics, Vol. 45, No. 3, August 2003)



Table of Contents
Preface.

Stochastic Processes: Description and Definition.

Markov chains.

Irreducible Markov Chains with Ergodic States.

Branching Processes and Other Special Topics.

Statistical Inference for Markov Chains.

Applied Markov Chains.

Simple Markov Processes.

Statistical Inference for Simple Markov Processes.

Applied Markov Processes.

Renewal Processes.

Stationary Processes and Time Series Analysis.

Simulation and Markov Chain Monte Carlo.

Answers to Selected Exercises.

Appendix.

Author Index.

Subject Index.

Applied Stochastic Processes 3e 378 Wiley Series

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    A Hardback by Gregory K. Miller, Gregory K. Miller


      View other formats and editions of Applied Stochastic Processes 3e 378 Wiley Series by Gregory K. Miller

      Publisher: Wiley
      Publication Date: 9/24/2002 12:00:00 AM
      ISBN13: 9780471414421, 978-0471414421
      ISBN10: 0471414425
      Also in:
      Mathematics

      Description

      Book Synopsis
      This third edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organizing it into a more teachable format. With more in-depth coverage of Markov chains and simple Markov process, the authors provide added emphasis to statistical inference in stochastic processes.

      Trade Review
      "…provides excellent coverage of the basic topics…Bhat and Miller have provided an excellent text and reference book.” (Interfaces, July/ August 2004)

      "...an extended and well-written introduction to the theory...of stochastic processes and their applications..." (Zentralblatt Math, Vol. 1024, 2004)

      "...besides conveying the concepts of stochastic processes, this book succeeds in providing insight into the reasons why for a particular topic certain lines of investigation are pursued and why certain variables/functions are introduced." (Technometrics, Vol. 45, No. 3, August 2003)



      Table of Contents
      Preface.

      Stochastic Processes: Description and Definition.

      Markov chains.

      Irreducible Markov Chains with Ergodic States.

      Branching Processes and Other Special Topics.

      Statistical Inference for Markov Chains.

      Applied Markov Chains.

      Simple Markov Processes.

      Statistical Inference for Simple Markov Processes.

      Applied Markov Processes.

      Renewal Processes.

      Stationary Processes and Time Series Analysis.

      Simulation and Markov Chain Monte Carlo.

      Answers to Selected Exercises.

      Appendix.

      Author Index.

      Subject Index.

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