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Abstract

Let X_1,...;X_n be independent observations on a random variable X. This paper considers a class of omnibus procedures for testing the hypothesis that the unknown distribution of X belongs to the family of Cauchy laws. The test statistics are weighted integrals of the squared modulus of the difference between the empirical characteristic function of the suitably standardized data and the characteristic function of the standard Cauchy distribution. A large-scale simulation study shows that the new tests compare favorably with the classical goodness-of-fit tests for the Cauchy distribution, based on the empirical distribution function. For small sample sizes and short-tailed alternatives, the uniformly most powerful invariant test of Cauchy versus normal beats all other tests under discussion. [PUBLICATION ABSTRACT]

Details

Title
Goodness-of-Fit Tests for the Cauchy Distribution Based on the Empirical Characteristic Function
Author
Gurtler, Nora; Henze, Norbert
Pages
267-286
Publication year
2000
Publication date
Jun 2000
Publisher
Springer Nature B.V.
ISSN
00203157
e-ISSN
15729052
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
214695680
Copyright
Copyright (c) 2000 Kluwer Academic Publishers