A CLASS OF NONPARAMETRIC TESTS FOR THE ONE-SAMPLE LOCATION PROBLEM

Autor:	K.L. Mehra, N.G.N. Prasad, K.S. Madhava Rao
Rok vydání:	1990
Předmět:	Statistics and Probability Independent and identically distributed random variables Statistics::Theory Wilcoxon signed-rank test Location parameter Kernel (statistics) Statistics Nonparametric statistics Sign test Point estimation Sign (mathematics) Mathematics
Zdroj:	Australian Journal of Statistics. 32:373-392
ISSN:	0004-9581
DOI:	10.1111/j.1467-842x.1990.tb01032.x
Popis:	Summary A class of “optimal”U-statistics type nonparametric test statistics is proposed for the one-sample location problem by considering a kernel depending on a constant a and all possible (distinct) subsamples of size two from a sample of n independent and identically distributed observations. The “optimal” choice of a is determined by the underlying distribution. The proposed class includes the Sign and the modified Wilcoxon signed-rank statistics as special cases. It is shown that any “optimal” member of the class performs better in terms of Pitman efficiency relative to the Sign and Wilcoxon-signed rank statistics. The effect of deviation of chosen a from the “optimal” a on Pitman efficiency is also examined. A Hodges-Lehmann type point estimator of the location parameter corresponding to the proposed “optimal” test-statistics is also defined and studied in this paper.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7b96aff24188c3fe74d92e4039bff384 https://doi.org/10.1111/j.1467-842x.1990.tb01032.x Zobrazit plný text záznamu Plný text