The Annals of Statistics

Transformed empirical processes and modified Kolmogorov-Smirnov tests for multivariate distributions

A. Cabaña and E. M. Cabaña

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Abstract

A general way of constructing classes of goodness-of-fit tests for multivariate samples is presented. These tests are based on a random signed measure that plays the same role as the empirical process in the construction of the classical Kolmogorov-Smirnov tests. The resulting tests are consistent against any fixed alternative, and, for each sequence of contiguous alternatives, a test in each class can be chosen so as to optimize the discrimination of those alternatives.

Article information

Source
Ann. Statist., Volume 25, Number 6 (1997), 2388-2409.

Dates
First available in Project Euclid: 30 August 2002

Permanent link to this document
https://projecteuclid.org/euclid.aos/1030741078

Digital Object Identifier
doi:10.1214/aos/1030741078

Mathematical Reviews number (MathSciNet)
MR1604469

Zentralblatt MATH identifier
0910.62044

Subjects
Primary: 62G10: Hypothesis testing 62G20: Asymptotic properties 62G30: Order statistics; empirical distribution functions 60G15: Gaussian processes

Keywords
Goodness-of-fit power improvement TEPs

Citation

Cabaña, A.; Cabaña, E. M. Transformed empirical processes and modified Kolmogorov-Smirnov tests for multivariate distributions. Ann. Statist. 25 (1997), no. 6, 2388--2409. doi:10.1214/aos/1030741078. https://projecteuclid.org/euclid.aos/1030741078


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