Stochastic Processes / Edition 2

Stochastic Processes / Edition 2

2.0 1
by Sheldon M. Ross
     
 

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ISBN-10: 0471120626

ISBN-13: 9780471120629

Pub. Date: 02/28/1995

Publisher: Wiley

A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter

Overview

A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.

Product Details

ISBN-13:
9780471120629
Publisher:
Wiley
Publication date:
02/28/1995
Series:
Wiley Series in Probability and Statistics
Edition description:
REV
Pages:
528
Product dimensions:
6.48(w) x 9.39(h) x 1.17(d)

Related Subjects

Table of Contents

Preliminaries.

The Poisson Process.

Renewal Theory.

Markov Chains.

Continuous-Time Markov Chains.

Martingales.

Random Walks.

Brownian Motion and Other Markov Processes.

Stochastic Order Relations.

Poisson Approximations.

Answers and Solutions to Selected Problems.

Index.

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Stochastic Processes 2 out of 5 based on 0 ratings. 1 reviews.
Anonymous More than 1 year ago
I did not find the book to have the same clarity of examples and explanation as I did with Sheldon Ross' "A First Course in Probability," - which I thouroughly enjoyed and gave a high rating. During the course that I took, I found myself referencing Ross' Probability Models book (better for an introductory course), and Taylor and Karlin's, "An introduction to Stochastic Modeling." Taylor and Karlin's book was the best by a good margin, I would highly recommend it and I used it almost exclusively towards the end of the course that I took.