Last edited by Gardatilar
Wednesday, July 29, 2020 | History

7 edition of Information theory and statistics found in the catalog.

Information theory and statistics

by Solomon Kullback

  • 208 Want to read
  • 29 Currently reading

Published by Dover Publications in Mineola, N.Y .
Written in English

    Subjects:
  • Mathematical statistics.,
  • Information theory.

  • Edition Notes

    StatementSolomon Kullback.
    SeriesDover books on mathematics
    Classifications
    LC ClassificationsQA276 .K8 1997
    The Physical Object
    Paginationxv, 399 p. :
    Number of Pages399
    ID Numbers
    Open LibraryOL668583M
    ISBN 100486696847
    LC Control Number97014382

    This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. The eventual goal is a general development of Shannon’s mathematical theoryFile Size: 1MB. Highly useful text studies the logarithmic measures of information and their application to testing statistical hypotheses. Topics include introduction and definition of measures of information, their relationship to Fisher’s information measure and sufficiency, fundamental inequalities of information theory, much more.

      Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography/5. Notes on Information Theory and Statistics b y Imre Csisz ar R en yi Institute of Mathematics Hungarian Academ y of Sciences POB H orner b o ok for information theory and Chapters Sections of the book Co x Hinc kley for statistical theory. Preliminaries The sym bol A f a j a A g denotes nite set of cardinalit y j x n m denotes the sequence File Size: KB.

    The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the books tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered . This tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The information measure known as information divergence or .


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Information theory and statistics by Solomon Kullback Download PDF EPUB FB2

Information Theory and Statistics and millions of other books are available for Amazon Kindle. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App.

Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device by: Topics include introduction and definition of measures of information, their relationship to Fisher's information measure and sufficiency, fundamental inequalities of information theory, much more.

Numerous worked examples and problems. /5(15). Kullback is well known for the famous Kullback-Liebler information measure of distance between distribution functions. This was the first statistics text to cover statistical methods from the information theory viewpoint and now stands as a classic.

For more recent developments see the text by Cover and Thomas/5(12). 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 by: As such, Information theory and statistics book 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. Information Theory and Statistics - Solomon Kullback - Google Books Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses.

Includes. Developed by Claude Shannon and Norbert Wiener in the late s, information theory, or statistical communication theory, deals with the theoretical underpinnings of a wide range of communication devices: radio, television, radar, computers, telegraphy, and more.

This book is an excellent introduction to the mathematics underlying the by: An Introduction To Information Theory () Behind the familiar surfaces of the telephone, radio, and television lies a sophisticated and intriguing body of knowledge known as information by: D.

Commenges/Information Theory and Statistics 3 cross-entropy, play a central role in statistics. The aim of this paper is to give an overview of applications of information theory in statistics, starting with the the basic de nitions.

More technical reviews can be found inEbrahimi et al. () andClarke et al.().Cited by: 3. The brief reviews below are from the "Further Reading" section of this book: "Information Theory: A Tutorial Introduction", by (me) JV Stone, published February Book's web page: Page on -- Applebaum D () 1.

Probability and In. Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and. COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to.

Based on lectures given by the author, this book focuses on providing reliable introductory explanations of key concepts of quantum information theory and quantum statistics - rather than on results.

The mathematically rigorous presentation is supported by numerous examples and exercises and by an appendix summarizing the relevant aspects of linear : Dénes Petz.

Information theory was developed to solve fundamental problems in the theory of communications, but its connections to statistical estimation and inference date nearly to.

Definition of information -- Properties of information -- Inequalities of information theory -- Limiting properties -- Information statistics -- Multinomial populations -- Poisson populations -- Contingency tables -- Multivariate normal populations -- The linear hypothesis -- Multivariate analysis: other hypothesis -- Linear discriminant functions.

This book is the Dover reprint of the original. It was probably ground-breaking in its day, but it is clearly showing its age now.

The first pages or so cover information theory and the rest are basically multivariate analysis/5(10). Now the book is published, these files will remain viewable on this website.

The same copyright rules will apply to the online copy of the book as apply to normal books. [e.g., copying the whole book onto paper is not permitted.] History: Draft - March 14 Draft - April 4 Draft - April 9 Draft - April Kullback is well known for the famous Kullback-Liebler information measure of distance between distribution functions.

This was the first statistics text to cover statistical methods from the information theory viewpoint and now stands as a classic. For more recent developments see the text by Cover and Thomas/5. This book is developed as a free, collaborative and interactive learning environment for elementary probability and statistics education.

The book blends information technology, scientific techniques and modern pedagogical concepts. ( views) A Minimum of Stochastics for Scientists by Noel Corngold - Caltech, The book introduces students to the ideas and. Abstract: 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 Cited by:.

Information theory is based on probability theory and statistics. Information theory often concerns itself with measures of information of the distributions associated with random variables.Highly useful text studies the logarithmic measures of information and their application to testing statistical hypotheses.

Topics include introduction and definition of measures of information, their relationship to Fisher's information measure and sufficiency, fundamental inequalities of information theory, much more.Essential Group Theory.

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