一类左删数据的拟合优度检验的统计威力

IF 0.6 Q4 STATISTICS & PROBABILITY

Austrian Journal of Statistics Pub Date : 2023-03-07 DOI:10.17713/ajs.v52i1.1348

M. Fusek

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引用次数: 2

摘要

一类双左删减数据经常出现在环境研究中。在本文中，考虑到各种样本量和审查程度，研究了最常用的拟合优度检验(Kolmogorov-Smirnov, cram -von Mises, Anderson-Darling)的功率。本文重点研究了未知参数下数据具有特定分布的复合假设的检验，使用极大似然法对未知参数进行估计。测试的性能是通过蒙特卡罗模拟几种分布来评估的，特别是威布尔分布、对数正态分布和伽马分布，这些分布是环境数据建模中最常用的分布。最后，这些试验用于鉴定麝香浓度在鱼组织中的分布。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Statistical Power of Goodness-of-Fit Tests for Type~I Left-Censored Data

Type I doubly left-censored data often arise in environmental studies. In this paper, the power of the most frequently used goodness-of-fit tests (Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling) is studied considering various sample sizes and degrees of censoring. Attention is paid to testing of the composite hypothesis that the data has a specific distribution with unknown parameters, which are estimated using the maximum likelihood method. Performance of the tests is assessed by means of Monte Carlo simulations for several distributions, specifically the Weibull, lognormal and gamma distributions, which are among the most frequently used distributions for modelling of environmental data. Finally, the tests are used for identification of the distribution of musk concentrations if fish tissue.

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来源期刊

Austrian Journal of Statistics STATISTICS & PROBABILITY-

CiteScore

1.10

自引率

0.00%

发文量

审稿时长

24 weeks

期刊介绍： The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.