Statistical power of goodness-of-fit tests for type I left-censored data
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Date
2023-03-07
Authors
Fusek, Michal
ORCID
0000-0002-9842-8384Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Austrian Statistical Society
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Abstract
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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Citation
Austrian Journal of Statistics. 2023, vol. 52, issue 1, p. 51-61.
https://www.ajs.or.at/index.php/ajs/article/view/1348
https://www.ajs.or.at/index.php/ajs/article/view/1348
Document type
Peer-reviewed
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Published version
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Language of document
en