Goodness-of-fit tests for the Cauchy distribution

Bora H. Onen, Dennis C. Dietz, Vincent C. Yen and Albert H. Moore
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Bora H. Onen: Air Force Institute of Technology, AFIT/EN
Dennis C. Dietz: Air Force Institute of Technology, AFIT/EN
Vincent C. Yen: Air Force Institute of Technology, AFIT/EN
Albert H. Moore: Air Force Institute of Technology, AFIT/EN

Computational Statistics, 2001, vol. 16, issue 1, No 5, 97-107

Abstract: Summary This article presents several modified goodness-of-fit tests for the Cauchy distribution with unknown location and scale parameters. Monte Carlo studies are performed to calculate critical values for several tests based on the empirical distribution function. Power studies suggest that the modified Kuiper (V) test is the most powerful standard test against most alternate distributions over a full range of sample sizes. A reflection technique is also employed which yields substantial improvement in the power of this test against symmetric distributions.

Keywords: Cauchy distribution; Goodness-of-fit; Monte Carlo; Kolmogorov-Smirnov test; Kuiper test (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s001800100053

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