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.
Publié le : 1978-05-14
Classification:
Asymptotic normality,
multivariate linear rank statistics,
non-i.i.d. case,
empirical df's,
62G10,
62G17
@article{1176344203,
author = {Ruymgaart, F. H. and van Zuijlen, M. C. A.},
title = {Asymptotic Normality of Multivariate Linear Rank Statistics in the Non-I.I.D. Case},
journal = {Ann. Statist.},
volume = {6},
number = {1},
year = {1978},
pages = { 588-602},
language = {en},
url = {http://dml.mathdoc.fr/item/1176344203}
}
Ruymgaart, F. H.; van Zuijlen, M. C. A. Asymptotic Normality of Multivariate Linear Rank Statistics in the Non-I.I.D. Case. Ann. Statist., Tome 6 (1978) no. 1, pp. 588-602. http://gdmltest.u-ga.fr/item/1176344203/