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First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources

The first- and second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to [Formula: see text] , is called th...

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Autores principales: Han, Te Sun, Nomura, Ryo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512691/
https://www.ncbi.nlm.nih.gov/pubmed/33265265
http://dx.doi.org/10.3390/e20030174
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author Han, Te Sun
Nomura, Ryo
author_facet Han, Te Sun
Nomura, Ryo
author_sort Han, Te Sun
collection PubMed
description The first- and second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to [Formula: see text] , is called the [Formula: see text]-optimum exponent. In this paper, we first give the second-order [Formula: see text]-optimum exponent in the case where the null hypothesis and alternative hypothesis are a mixed memoryless source and a stationary memoryless source, respectively. We next generalize this setting to the case where the alternative hypothesis is also a mixed memoryless source. Secondly, we address the first-order [Formula: see text]-optimum exponent in this setting. In addition, an extension of our results to the more general setting such as hypothesis testing with mixed general source and a relationship with the general compound hypothesis testing problem are also discussed.
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spelling pubmed-75126912020-11-09 First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources Han, Te Sun Nomura, Ryo Entropy (Basel) Article The first- and second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to [Formula: see text] , is called the [Formula: see text]-optimum exponent. In this paper, we first give the second-order [Formula: see text]-optimum exponent in the case where the null hypothesis and alternative hypothesis are a mixed memoryless source and a stationary memoryless source, respectively. We next generalize this setting to the case where the alternative hypothesis is also a mixed memoryless source. Secondly, we address the first-order [Formula: see text]-optimum exponent in this setting. In addition, an extension of our results to the more general setting such as hypothesis testing with mixed general source and a relationship with the general compound hypothesis testing problem are also discussed. MDPI 2018-03-06 /pmc/articles/PMC7512691/ /pubmed/33265265 http://dx.doi.org/10.3390/e20030174 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Han, Te Sun
Nomura, Ryo
First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title_full First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title_fullStr First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title_full_unstemmed First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title_short First- and Second-Order Hypothesis Testing for Mixed Memoryless Sources
title_sort first- and second-order hypothesis testing for mixed memoryless sources
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512691/
https://www.ncbi.nlm.nih.gov/pubmed/33265265
http://dx.doi.org/10.3390/e20030174
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