数据驱动的Poissonity有效分数测试

IF 0.4 4区数学 Q4 STATISTICS & PROBABILITY

Probability and Mathematical Statistics-Poland Pub Date : 2019-06-10 DOI:10.19195/0208-4147.39.1.8

T. Inglot

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引用次数: 2

摘要

提出了一种新的数据驱动分数检验泊松分布拟合优度的方法。它们是Inglot等人在1997年开发的复合假设的数据驱动拟合优度检验的一般构造的直接应用。通过模拟研究表明，这些测试在标准替代方案中表现得几乎与最知名的解决方案一样好，并且在更困难的替代方案中表现得更好。

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Data driven efficient score tests for Poissonity

New data driven score tests for testing goodness of fit of the Poisson distribution are proposed. They are direct applications of the general construction of data driven goodness-of-fit tests for composite hypotheses developed in Inglot et al. 1997. By a simulation study it is shown that these tests perform almost equally well as the best known solutions for standard alternatives and outperform them for more difficult alternatives.

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来源期刊

Probability and Mathematical Statistics-Poland STATISTICS & PROBABILITY-

CiteScore

0.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： PROBABILITY AND MATHEMATICAL STATISTICS is published by the Kazimierz Urbanik Center for Probability and Mathematical Statistics, and is sponsored jointly by the Faculty of Mathematics and Computer Science of University of Wrocław and the Faculty of Pure and Applied Mathematics of Wrocław University of Science and Technology. The purpose of the journal is to publish original contributions to the theory of probability and mathematical statistics.