The notion of efficient test for a Euclidean parameter in a semiparametric model was introduced by Stein [Proc. Third Berkeley Symp. Math. Statist. Probab.
1 (1956) 187-195]. Such tests are locally most powerful for a wide class of infinite-dimensional nuisance parameters. The first formal application of this notion to a suitably parametrized two-sample problem was provided by Hájek [Ann. Math. Statist.
33 (1962) 1124-1147]. However, this and subsequent solutions appear to be not well-suited for practical applications. This article aims to show that an adaptive two-sample test introduced recently by Janic-Wróblewska and Ledwina [Scand. J. Statist.
27 (2000) 281-297] is locally most powerful under a more realistic setting.
Publié le : 2003-12-14
Classification:
Adaptive test,
efficient test,
model selection,
nonparametric test,
two-sample problem,
62G10,
62G20,
62G99
@article{1074290336,
author = {Ducharme, Gilles R. and Ledwina, Teresa},
title = {Efficient and adaptive nonparametric test for the two-sample problem},
journal = {Ann. Statist.},
volume = {31},
number = {1},
year = {2003},
pages = { 2036-2058},
language = {en},
url = {http://dml.mathdoc.fr/item/1074290336}
}
Ducharme, Gilles R.; Ledwina, Teresa. Efficient and adaptive nonparametric test for the two-sample problem. Ann. Statist., Tome 31 (2003) no. 1, pp. 2036-2058. http://gdmltest.u-ga.fr/item/1074290336/