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Autor principal: Chen, Xiongzhi
Formato: Preprint
Publicado: 2019
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Acceso en línea:https://arxiv.org/abs/1906.10246
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author Chen, Xiongzhi
author_facet Chen, Xiongzhi
contents We consider estimating the proportion of random variables for two types of composite null hypotheses: (i) the means of the random variables belonging to a non-empty, bounded interval; (ii) the means of the random variables belonging to an unbounded interval that is not the whole real line. For each type of composite null hypotheses, uniformly consistent estimators of the proportion of false null hypotheses are constructed for random variables whose distributions are members of the Gamma family. Further, uniformly consistent estimators of certain functions of a bounded null on the means are provided for the random variables mentioned earlier. These functions are continuous and of bounded variation. The estimators are constructed via solutions to Lebesgue-Stieltjes integral equations and harmonic analysis, do not rely on a concept of p-value, and have various applications.ce via mixture models, and may be used to estimate the sparsity level in high-dimensional Gaussian linear models.
format Preprint
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institution arXiv
publishDate 2019
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spellingShingle Uniformly consistent proportion estimation for composite hypotheses via integral equations: "the case of Gamma random variables"
Chen, Xiongzhi
Statistics Theory
Probability
62F12, 42A38, 45H05
We consider estimating the proportion of random variables for two types of composite null hypotheses: (i) the means of the random variables belonging to a non-empty, bounded interval; (ii) the means of the random variables belonging to an unbounded interval that is not the whole real line. For each type of composite null hypotheses, uniformly consistent estimators of the proportion of false null hypotheses are constructed for random variables whose distributions are members of the Gamma family. Further, uniformly consistent estimators of certain functions of a bounded null on the means are provided for the random variables mentioned earlier. These functions are continuous and of bounded variation. The estimators are constructed via solutions to Lebesgue-Stieltjes integral equations and harmonic analysis, do not rely on a concept of p-value, and have various applications.ce via mixture models, and may be used to estimate the sparsity level in high-dimensional Gaussian linear models.
title Uniformly consistent proportion estimation for composite hypotheses via integral equations: "the case of Gamma random variables"
topic Statistics Theory
Probability
62F12, 42A38, 45H05
url https://arxiv.org/abs/1906.10246