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) - USK Library, accessed September 10, 2024, http://uilis.usk.ac.id/oer/items/show/4773.