Overview
- First book on chaos from a statistical perspective
Part of the book series: Springer Series in Statistics (SSS)
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Table of contents (7 chapters)
Keywords
About this book
Reviews
From the reviews:
SHORT BOOK REVIEWS
"The authors have done an excellent job, providing an overview of known results with detailed references to the literature, as well as pointing out some open problems. In general, the book serves to ‘encourage more statisticians to join in with the fun of chaos’."
"The book fills a gap in the need to overview the present state of statistics and to point into the right direction for research. It seems to me that this has been achieved by the authors in an excellent way. Chan and Tong’s book certainly deserves recommendation to anyone who is interested in dynamics, either as a statistician or as a researcher in the theory of dynamical systems, ergodic theory or differential equations." (Manfred Denker, Metrika, September, 2003)
"The authors fully attain their aim stated in the introduction. Their style is very friendly and they take much care to prevent technical details from obscuring the essential issues. The book requires careful reading but the profit is well worth the effort. A truly enjoyable and recommendable book!" (Ricardo Maronna, Statistical Papers, Vol. 44 (1), 2003)
Authors and Affiliations
Bibliographic Information
Book Title: Chaos: A Statistical Perspective
Authors: Kung-Sik Chan, Howell Tong
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/978-1-4757-3464-5
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag New York 2001
Hardcover ISBN: 978-0-387-95280-2Published: 09 August 2001
Softcover ISBN: 978-1-4419-2936-5Published: 23 November 2010
eBook ISBN: 978-1-4757-3464-5Published: 09 March 2013
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XVI, 300
Topics: Statistical Theory and Methods, Computational Intelligence, Math. Applications in Chemistry, Complex Systems, Probability Theory and Stochastic Processes, Statistical Physics and Dynamical Systems