New Developments in Statistical Information Theory Based on Entropy and Divergence Measures
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, base...
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| Year of Publication: | 2019 |
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| Physical Description: | 1 electronic resource (344 p.) |
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Pardo, Leandro auth New Developments in Statistical Information Theory Based on Entropy and Divergence Measures MDPI - Multidisciplinary Digital Publishing Institute 2019 1 electronic resource (344 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier 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. English mixture index of fit Kullback-Leibler distance relative error estimation minimum divergence inference Neyman Pearson test influence function consistency thematic quality assessment asymptotic normality Hellinger distance nonparametric test Berstein von Mises theorem maximum composite likelihood estimator 2-alternating capacities efficiency corrupted data statistical distance robustness log-linear models representation formula goodness-of-fit general linear model Wald-type test statistics Hölder divergence divergence logarithmic super divergence information geometry sparse robust estimation relative entropy minimum disparity methods MM algorithm local-polynomial regression association models total variation Bayesian nonparametric ordinal classification variables Wald test statistic Wald-type test composite hypotheses compressed data hypothesis testing Bayesian semi-parametric single index model indoor localization composite minimum density power divergence estimator quasi-likelihood Chernoff Stein lemma composite likelihood asymptotic property Bregman divergence robust testing misspecified hypothesis and alternative least-favorable hypotheses location-scale family correlation models minimum penalized ?-divergence estimator non-quadratic distance robust semiparametric model divergence based testing measurement errors bootstrap distribution estimator generalized renyi entropy minimum divergence methods generalized linear model ?-divergence Bregman information iterated limits centroid model assessment divergence measure model check two-sample test Wald statistic 3-03897-936-8 |
| language |
English |
| format |
eBook |
| author |
Pardo, Leandro |
| spellingShingle |
Pardo, Leandro New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| author_facet |
Pardo, Leandro |
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l p lp |
| author_sort |
Pardo, Leandro |
| title |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_full |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_fullStr |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_full_unstemmed |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_auth |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_new |
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| title_sort |
new developments in statistical information theory based on entropy and divergence measures |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2019 |
| physical |
1 electronic resource (344 p.) |
| isbn |
3-03897-937-6 3-03897-936-8 |
| illustrated |
Not Illustrated |
| work_keys_str_mv |
AT pardoleandro newdevelopmentsinstatisticalinformationtheorybasedonentropyanddivergencemeasures |
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(CKB)4920000000095103 (oapen)https://directory.doabooks.org/handle/20.500.12854/54566 (EXLCZ)994920000000095103 |
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cr |
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New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
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1796652272562733056 |
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