A First Course in Stochastic Processes, 2nd Edition

 
A First Course in Stochastic Processes, 2nd Edition,Samuel Karlin,Howard Taylor,ISBN9780123985521
 
 
 

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Academic Press

9780123985521

9780080570419

557

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Description

The purpose, level, and style of this new edition conform to the tenets set forth in the original preface. The authors continue with their tack of developing simultaneously theory and applications, intertwined so that they refurbish and elucidate each other.
The authors have made three main kinds of changes. First, they have enlarged on the topics treated in the first edition. Second, they have added many exercises and problems at the end of each chapter. Third, and most important, they have supplied, in new chapters, broad introductory discussions of several classes of stochastic processes not dealt with in the first edition, notably martingales, renewal and fluctuation phenomena associated with random sums, stationary stochastic processes, and diffusion theory.

Readership

Undergraduate and graduate students studying mathematics.

Samuel Karlin

Affiliations and Expertise

Stanford University and The Weizmann Institute of Science

View additional works by Samuel Karlin

Howard Taylor

Howard E. Taylor is a research chemist with the National Research Program, Water Resources Division, U.S. Geological Survey located in Boulder, Colorado. Dr. Taylor has played a major role over the past 25 years in the development of plasma spectrometric techniques in analytical chemistry, as reflected in his more than 150 technical publications and the presentation of numerous papers at national and international technical meetings. He has served as faculty affiliate at Colorado State University and has taught American Chemical Society Short Courses for more than 15 years.

Affiliations and Expertise

U.S. Geological Survey, Boulder, Colorado, U.S.A.

View additional works by Howard E. Taylor

A First Course in Stochastic Processes, 2nd Edition

Preface. Elements of Stochastic Processes. Markov Chains. The Basic Limit Theorem of Markov Chains and Applications. Classical Examples of Continuous Time Markov Chains. Renewal Processes. Martingales. Brownian Motion. Branching Processes. Stationary Processes. Review of Matrix Analysis. Index.
 
 
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