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May, 1978 Asymptotic Normality of Multivariate Linear Rank Statistics in the Non-I.I.D. Case
F. H. Ruymgaart, M. C. A. van Zuijlen
Ann. Statist. 6(3): 588-602 (May, 1978). DOI: 10.1214/aos/1176344203

Abstract

Asymptotic normality is established for multivariate linear rank statistics of general type in the non-i.i.d. case covering null hypotheses as well as almost arbitrary alternatives. The functions generating the regression constants and the scores are allowed to have a finite number of discontinuities of the first kind, and to tend to infinity near 0 and 1. The proof is based on properties of empirical df's in the non-i.i.d. case and is patterned on the 1958 Chernoff-Savage method. As special cases e.g. rank statistics used for testing against regression and rank statistics for testing independence are included.

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F. H. Ruymgaart. M. C. A. van Zuijlen. "Asymptotic Normality of Multivariate Linear Rank Statistics in the Non-I.I.D. Case." Ann. Statist. 6 (3) 588 - 602, May, 1978. https://doi.org/10.1214/aos/1176344203

Information

Published: May, 1978
First available in Project Euclid: 12 April 2007

zbMATH: 0408.62042
MathSciNet: MR464489
Digital Object Identifier: 10.1214/aos/1176344203

Subjects:
Primary: 62G10
Secondary: 62G17

Keywords: asymptotic normality , empirical df's , multivariate linear rank statistics , non-i.i.d. case

Rights: Copyright © 1978 Institute of Mathematical Statistics

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Vol.6 • No. 3 • May, 1978
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