Overview

This practical and accessible text enables students in engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes. The author provides user-friendly, yet rigorous coverage. He demonstrates both numerical and analytical solution methods in detail and includes numerous worked examples and exercises.

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9781439808757

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Reviews

! an accessible, well paced, and very nicely presented book. The publishers are also to be commended on its nice production: it is the sort of book which is a pleasure to read. In all, it is an excellent textbook for use in introductory courses on stochastic processes. --International Statistical Review (2010), 78, 3 Praise for the First Edition ! a beautiful introductory textbook on stochastic processes ! Plenty of applications, examples, and exercises bring the reader to the intuitive understanding of the subject. --Zentralblatt MATH Well-chosen examples and interesting exercises make this text a good choice for a first course in stochastic processes for a broad class of students. --Journal of the American Statistical Association

This book provides insight on the mathematical methods for modelling and understanding real-world processes. ! for the teacher, this book provides an abundant resource of examples for class exercises and student homework. The modelling examples include many that would be of interest for advanced undergraduate courses on inventory management, reliability, operations management and queuing networks. ! This is a book for the few who would like to know almost everything about stochastic processes and for the many who need to know something, and would like to have their eyes opened to the many models and analytical results available on stochastic processes. --J. Smart, Journal of the Operational Research Society, Vol. 62, 2011 This book is written by a well-experienced scientist and teacher. The material is carefully chosen and presented in a systematic way, starting with the basics and reaching more advanced topics. ! It is very useful to see a large number of examples worked out in detail. Thus, besides university courses, the book can be successfully used for self-education. ! This book is a good example of how to write on sophisticated topics about stochastic processes without involving the heavy measure theoretic machinery. Another advantage of the book is the application-oriented approach that is followed by the author. ! This book can be strongly recommended for introductory, intermediate or advanced university courses on stochastic processes. Both students and their teachers may benefit considerably from it. --Journal of the Royal Statistical Society: Series A, July 2011 ! an accessible, well paced, and very nicely presented book. The publishers are also to be commended on its nice production: it is the sort of book which is a pleasure to read. In all, it is an excellent textbook for use in introductory courses on stochastic processes. --International Statistical Review (2010), 78, 3 This book may be recommended for all readers who want to understand, build and analyse stochastic models and relevant problems. --Zentralblatt MATH 1191 Praise for the First Edition: ! a beautiful introductory textbook on stochastic processes ! Plenty of applications, examples, and exercises bring the reader to the intuitive understanding of the subject. --Zentralblatt MATH Well-chosen examples and interesting exercises make this text a good choice for a first course in stochastic processes for a broad class of students. --Journal of the American Statistical Association

This book is written by a well-experienced scientist and teacher. The material is carefully chosen and presented in a systematic way, starting with the basics and reaching more advanced topics. ! It is very useful to see a large number of examples worked out in detail. Thus, besides university courses, the book can be successfully used for self-education. ! This book is a good example of how to write on sophisticated topics about stochastic processes without involving the heavy measure theoretic machinery. Another advantage of the book is the application-oriented approach that is followed by the author. ! This book can be strongly recommended for introductory, intermediate or advanced university courses on stochastic processes. Both students and their teachers may benefit considerably from it. --Journal of the Royal Statistical Society: Series A, July 2011 ! an accessible, well paced, and very nicely presented book. The publishers are also to be commended on its nice production: it is the sort of book which is a pleasure to read. In all, it is an excellent textbook for use in introductory courses on stochastic processes. --International Statistical Review (2010), 78, 3 This book may be recommended for all readers who want to understand, build and analyse stochastic models and relevant problems. --Zentralblatt MATH 1191 Praise for the First Edition: ! a beautiful introductory textbook on stochastic processes ! Plenty of applications, examples, and exercises bring the reader to the intuitive understanding of the subject. --Zentralblatt MATH Well-chosen examples and interesting exercises make this text a good choice for a first course in stochastic processes for a broad class of students. --Journal of the American Statistical Association

Author Information

Vidyadhar G. Kulkarni is a Norman Johnson Professor in the Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill.

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