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CRC Press Statistical Inference Based on Divergence Measures - CRC Press

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Description

Statistical Inference Based on Divergence Measures is a comprehensive textbook that explores classical problems of statistical inference through the lens of entropy and divergence measures. This volume, part of the Statistics: A Series of Textbooks and Monographs collection, demonstrates how functionals from information theory can provide powerful alternatives to traditional likelihood ratio tests and Pearson-type statistics, particularly in discrete models. The text bridges a gap in statistical education by presenting divergence statistics as a sophisticated approach that many statisticians overlook, despite its proven effectiveness. Written by subject experts, this resource is essential for graduate students and researchers seeking to understand and apply divergence-based methods in estimation and hypothesis testing.

Key Features

Covers classical statistical inference problems including estimation and hypothesis testing using divergence measures.

Presents divergence statistics as powerful alternatives to traditional likelihood ratio tests and Pearson-type statistics.

Part of the Statistics: A Series of Textbooks and Monographs collection by Chapman and Hall/CRC.

Explores functionals of information theory such as entropies and divergences in practical statistical applications.

Designed for graduate-level study in higher education mathematics and statistics programmes.

Product Specifications

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

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