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Information theory and statistics : a tutorial

	Author(s):	Imre Csisz´ar, Paul Shields
	Collection:	Foundations and Trends in Communications and Information Theory
	Publisher:	Now Publishers Inc
	Year:	2004
	Language:	English
	Pages:	122 pages
	Size:	1.03 MB
	Extension:	PDF

[tab] [content title="Description"]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. [/content] [content title="Content"] [/content] [content title="About the author"] Paul Shields is an American mathematician.Imre Csiszár (Hungarian: [ˈimrɛ ˈt͡ʃisaːr]) is a Hungarian mathematician with contributions to information theory and probability theory. In 1996 he won the Claude E. Shannon Award, the highest annual award given in the field of information theory. He was born on February 7, 1938, in Miskolc, Hungary. He became interested in mathematics in middle school. He was inspired by his father who was a forest engineer and was among the first to use mathematical techniques in his area. He studied mathematics at the Eötvös Loránd University, Budapest, and received his Diploma in 1961. He got his PhD in 1967 and the scientific degree Doctor of Mathematical Science in 1977. [/content] [/tab]

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