New Developments in Statistical Information Theory Based on Entropy and Divergence Measures

Dublin Core

Title

New Developments in Statistical Information Theory Based on Entropy and Divergence Measures

Subject

Social Sciences

Description

This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations.

Creator

Pardo, Leandro

Source

https://www.mdpi.com/books/pdfview/book/1298

Publisher

MDPI - Multidisciplinary Digital Publishing Institute

Date

2019

Contributor

Baihaqi

Rights

Creative Commons

Format

PDF

Language

English

Type

Textbooks

Files

Collection

Citation

Pardo, Leandro, “New Developments in Statistical Information Theory Based on Entropy and Divergence Measures,” Open Educational Resource (OER) - Unsyiah Library, accessed October 2, 2022, http://uilis.unsyiah.ac.id/oer/items/show/4773.

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