Elements of Applied Stochastic Processes

Inbunden, Engelska, 2002

Del 378 i serien Wiley Series in Probability and Statistics

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Beskrivning

This 3rd edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organising it into a more teachable format. It provides more in-depth coverage of Markov chains and simple Markov process and gives added emphasis to statistical inference in stochastic processes. Integration of theory and application offers improved teachability Provides a comprehensive introduction to stationary processes and time series analysis Integrates a broad set of applications into the text Utilizes a wealth of examples from research papers and monographs

Produktinformation

Utgivningsdatum:2002-09-24
Mått:163 x 241 x 32 mm
Vikt:894 g
Format:Inbunden
Språk:Engelska
Serie:Wiley Series in Probability and Statistics
Antal sidor:488
Upplaga:3
Förlag:John Wiley & Sons Inc
ISBN:9780471414421

Utforska kategorier

Tillämpad matematik inom Naturvetenskap och teknik

Mer om författaren

U. NARAYAN BHAT, PhD, is Professor of Statistical Science and Operations Research as well as the Dean of Research and Graduate Studies at Southern Methodist University. GREGORY K. MILLER, PhD, is Associate Professor of Statistics at Stephen F. Austin State University.

Recensioner i media

"…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)

Innehållsförteckning

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.