Authors:
Enables readers to develop accurate mathematical models of systems that evolve randomly in time
Reader able to use the stochastic models developed in the book to design systems to achieve preferred performance targets
Includes large number of examples and detailed case studies that provide an easy way to understand the concepts and the methodologies of stochastic modeling
Includes supplementary material: sn.pub/extras
Part of the book series: Springer Texts in Statistics (STS)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (7 chapters)
-
Front Matter
-
Back Matter
About this book
Reviews
From the reviews of the second edition:
“The author has added a new chapter on Poisson processes and another one on Brownian motion. The discussion is kept on an elementary level and does not require any knowledge from measure theory or advanced calculus. … the text is suitable for an undergraduate course on probabilistic modeling for students from physics, engineering, operations research, computer science, business administration or some related field that needs advanced modeling techniques.” (H. M. Mai, Zentralblatt MATH, Vol. 1222, 2011)
“Suitable for undergraduates in Mathematics, Statistics, Operations Research, Computer Science, Business Administration, Public Policy, etc. This is a very clear and readable text on Markov chains, Poisson processes, continuous time Markov chains, renewal processes, and queuing processes. … The treatment is very clear, intuitive as well as rigorous, without being pedantic, and full of interesting examples and case studies. … The book should be fun to teach from and learn from.” (Jayanta K. Ghosh, International Statistical Review, Vol. 80 (3), 2012)
Authors and Affiliations
-
, Dept. of Operations Research, University of North Carolina, Chapel Hill, USA
V. G. Kulkarni
About the author
Bibliographic Information
Book Title: Introduction to Modeling and Analysis of Stochastic Systems
Authors: V. G. Kulkarni
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-1-4419-1772-0
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4419-1771-3Published: 10 November 2010
Softcover ISBN: 978-1-4614-2735-3Published: 27 December 2012
eBook ISBN: 978-1-4419-1772-0Published: 03 November 2010
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 2
Number of Pages: XIII, 313
Topics: Statistics, general, Probability Theory and Stochastic Processes, Operations Research/Decision Theory