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

Name: New Developments in Statistical Information Theory Based on Entropy and Divergence Measures
Brand: MDPI AG
Availability: OutOfStock
Rating: 5 (1 reviews)

By Leandro Pardo

0 - Default Title

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. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.

Product details

Binding:

Paperback

Edition:

illustrated

Number of Pages:

344

Release Date:

2019-05-20

Publication Date:

2019-05-20

Publisher:

MDPI AG

Languages:

Original: English

ISBN10:

3038979368

ISBN13:

9783038979364

GPSR Manufacturer Reference:

[email protected]

Weight:

880 g

Height:

170 cm

Width:

244 cm

Thickness:

22 cm

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