Information Theory And Statistics: A Tutorial

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Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an in-depth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highly-important topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.

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Information Theory and Statistics: A Tutorial Information Theory and Statistics: A Tutorial Imre Csisz´ ar R´ enyi Institute of Mathematics, Hungarian Academy of Sciences POB 127, H-1364 Budapest, Hungary [email protected] Paul C. Shields Professor Emeritus of Mathematics, University of Toledo, Ohio, USA [email protected] Boston – Delft R in Foundations and Trends Communications and Information Theory Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 USA Tel. +1 781 871 0245 www.nowpublishers.com
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