An Adaptive Multivariate Signed-Rank Test For The One-Sample Location Problem

Research output: Contribution to journalArticle

Abstract

A multivariate affine-invariant adaptive test procedure is proposed for the one-sample location problem. The procedure suggested uses the multivariate sign test based on interdirections suggested by Randles, a multivariate signed-rank procedure suggested by Peters and Randles, and a light-tailed version of the signed-rank procedure. A selection statistic constructed from univariate Mahalanobis distances is used to choose the appropriate sign or signed-rank procedure yielding a large sample test which performs well for a broad class of distributions. The performance of the adaptive procedure is assessed via Monte Carlo simulation results.

Original languageEnglish (US)
Pages (from-to)157-163
Number of pages7
JournalJournal of Nonparametric Statistics
Volume1
Issue number1-2
DOIs
Publication statusPublished - Jan 1 1991
Externally publishedYes

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Keywords

  • Adaptive
  • affine-invariant
  • location
  • multivariate
  • sign test
  • signed-rank test

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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