£133.40

CRC Press Statistical Inference Based on Divergence Measures 185

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Description

Expand your mathematical knowledge with Statistical Inference Based on Divergence Measures, part of the Statistics: A Series of Textbooks and Monographs collection by CRC Press. While the use of information theory functionals like entropy and divergence in statistical inference is established, many practitioners are still unfamiliar with the potential of this methodology. This text provides a deep look into how divergence statistics serve as a strong alternative to classical likelihood ratio tests and Pearson-type statistics in discrete models. By focusing on measures of entropy and divergence, the book addresses fundamental problems in statistical inference, including estimation and hypothesis testing. It is an essential resource for those looking to bridge the gap between information theory and classical statistical methods.

Key Features

Explores classical statistical inference problems such as estimation and hypothesis testing using entropy and divergence measures.

Provides a detailed look at divergence statistics as a functional alternative to the classical likelihood ratio test.

Covers advanced concepts in information theory applied to discrete models and Pearson-type statistics.

Part of the recognized Statistics: A Series of Textbooks and Monographs collection from CRC Press.

Designed for higher education and professional research in the fields of mathematics and statistics.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
10 October 2005
Listed Since
05 February 2007

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No barcode data available

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