基于积分方程的复合假设的一致一致比例估计:“Gamma随机变量的情况”

IF 0.6 4区 数学 Q3 STATISTICS & PROBABILITY
Xiongzhi Chen
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引用次数: 0

摘要

我们考虑对两类复合零假设估计随机变量的比例:(i)属于非空有界区间的随机变量的均值;(ii)属于非整条实线的无界区间的随机变量的均值。对于每种类型的复合零假设,对于其分布为Gamma族成员的随机变量,构造了假零假设比例的一致一致估计。此外,对于前面提到的随机变量,给出了均值上有界null的某些函数的一致一致估计。这些函数是连续的,变化有界。估计量是通过Lebesgue-Stieltjes积分方程的解和调和分析构造的,不依赖于p值的概念,并且具有各种应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uniformly consistent proportion estimation for composite hypotheses via integral equations: “the case of Gamma random variables”

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.

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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: Annals of the Institute of Statistical Mathematics (AISM) aims to provide a forum for open communication among statisticians, and to contribute to the advancement of statistics as a science to enable humans to handle information in order to cope with uncertainties. It publishes high-quality papers that shed new light on the theoretical, computational and/or methodological aspects of statistical science. Emphasis is placed on (a) development of new methodologies motivated by real data, (b) development of unifying theories, and (c) analysis and improvement of existing methodologies and theories.
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