Elements of Applied Stochastic Processes

Praise for THE SECOND EDITION
"A valuable contribution . . . rigorous and carefully thought out."
–Zeitschrift fur Operations Research
A state–of–the–art text on stochastic models and their applications
Much has changed in the field of stochastic modeling since the highly successful Second Edition of this popular text. In response, the authors have significantly revised their book to deliver a thoroughly up–to–date overview of the field.
This Third Edition of Elements of Applied Stochastic Processes provides a basic understanding of the fundamental theory of stochastic processes. Topics include Markov chains, and Markov, branching, renewal, and stationary processes, all of which are illustrated with the rich diversity of actual applications. Restructured to enhance the book’s usefulness for practicing professionals, students, and instructors, this edition features two chapters dedicated entirely to applications from journal articles and new material on statistical inference for stochastic processes, with inference on queues as an area of application. Also new is a chapter on simulation and Markov Chain Monte Carlo.
This updated new edition:Retains the bridge between theory and application while improving teachabilityIntegrates a broad set of applications into the textProvides expanded coverage on statistical inference for stochastic processesUtilizes a wealth of examples from research papers and monographsOffers a comprehensive introduction to stationary processes and time series analysis

Spis treści:
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.

Nota biograficzna:
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.

Okładka tylna:
Praise for THE SECOND EDITION
"A valuable contribution . . . rigorous and carefully thought out."
–Zeitschrift fur Operations Research
A state–of–the–art text on stochastic models and their applications
Much has changed in the field of stochastic modeling since the highly successful Second Edition of this popular text. In response, the authors have significantly revised their book to deliver a thoroughly up–to–date overview of the field.
This Third Edition of Elements of Applied Stochastic Processes provides a basic understanding of the fundamental theory of stochastic processes. Topics include Markov chains, and Markov, branching, renewal, and stationary processes, all of which are illustrated with the rich diversity of actual applications. Restructured to enhance the book’s usefulness for practicing professionals, students, and instructors, this edition features two chapters dedicated entirely to applications from journal articles and new material on statistical inference for stochastic processes, with inference on queues as an area of application. Also new is a chapter on simulation and Markov Chain Monte Carlo.
This updated new edition:Retains the bridge between theory and application while improving teachabilityIntegrates a broad set of applications into the textProvides expanded coverage on statistical inference for stochastic processesUtilizes a we alth of examples from research papers and monographsOffers a comprehensive introduction to stationary processes and time series analysis