Power comparisons of the unbiased Berk-Jones test and the unbiased reversed Berk-Jones test

The Berk-Jones test and the reversed Berk-Jones test are shown to be biased by computing the exact minimum power with confidence bands for the continuous distribution function. The bias correction is applied to the Berk-Jones test and the reversed Berk-Jones test by using a similar process of Frey (...

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Published inCommunications in statistics. Simulation and computation Vol. 50; no. 4; pp. 1009 - 1024
Main Authors Hanyuda, Bunto, Murakami, Hidetoshi
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 16.04.2021
Taylor & Francis Ltd
Subjects
Berk-Jones test
Bias correction
Confidence band
Continuity (mathematics)
Distribution functions
Power
Reversed Berk-Jones test
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ISSN0361-0918
1532-4141
DOI10.1080/03610918.2019.1571608

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Abstract The Berk-Jones test and the reversed Berk-Jones test are shown to be biased by computing the exact minimum power with confidence bands for the continuous distribution function. The bias correction is applied to the Berk-Jones test and the reversed Berk-Jones test by using a similar process of Frey ( 2009 ). In order to compose the unbiased test, various critical values are listed. Simulations are used to compare the power of the biased and unbiased Berk-Jones and reversed Berk-Jones tests for various population distributions. Numerical results indicate that the unbiased Berk-Jones test is more powerful than the unbiased reversed Berk-Jones test.
AbstractList The Berk-Jones test and the reversed Berk-Jones test are shown to be biased by computing the exact minimum power with confidence bands for the continuous distribution function. The bias correction is applied to the Berk-Jones test and the reversed Berk-Jones test by using a similar process of Frey ( 2009 ). In order to compose the unbiased test, various critical values are listed. Simulations are used to compare the power of the biased and unbiased Berk-Jones and reversed Berk-Jones tests for various population distributions. Numerical results indicate that the unbiased Berk-Jones test is more powerful than the unbiased reversed Berk-Jones test.
The Berk-Jones test and the reversed Berk-Jones test are shown to be biased by computing the exact minimum power with confidence bands for the continuous distribution function. The bias correction is applied to the Berk-Jones test and the reversed Berk-Jones test by using a similar process of Frey (2009). In order to compose the unbiased test, various critical values are listed. Simulations are used to compare the power of the biased and unbiased Berk-Jones and reversed Berk-Jones tests for various population distributions. Numerical results indicate that the unbiased Berk-Jones test is more powerful than the unbiased reversed Berk-Jones test.
Author Murakami, Hidetoshi
Hanyuda, Bunto
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Snippet The Berk-Jones test and the reversed Berk-Jones test are shown to be biased by computing the exact minimum power with confidence bands for the continuous...
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SubjectTerms Berk-Jones test
Bias correction
Confidence band
Continuity (mathematics)
Distribution functions
Power
Reversed Berk-Jones test
Title Power comparisons of the unbiased Berk-Jones test and the unbiased reversed Berk-Jones test
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