Austrian Journal of Statistics | |
Statistical Power of Goodness-of-Fit Tests for Type~I Left-Censored Data | |
article | |
Michal Fusek1  | |
[1] Brno University of Technology | |
关键词: censored data; goodness-of-fit test; empirical power; type I left-censoring.; | |
DOI : 10.17713/ajs.v52i1.1348 | |
学科分类:医学(综合) | |
来源: Austrian Statistical Society | |
【 摘 要 】
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.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO202307120004736ZK.pdf | 501KB | download |