z-logo
Premium
Data depth‐based nonparametric scale tests
Author(s) -
Chenouri Shojaeddin,
Small Christopher G.,
Farrar Thomas J.
Publication year - 2011
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.10099
Subject(s) - mathematics , nonparametric statistics , statistics , percentile , sample size determination , combinatorics , humanities , philosophy
Liu and Singh (1993, 2006) introduced a depth‐based d ‐variate extension of the nonparametric two sample scale test of Siegel and Tukey (1960). Liu and Singh (2006) generalized this depth‐based test for scale homogeneity of k  ≥ 2 multivariate populations. Motivated by the work of Gastwirth (1965), we propose k sample percentile modifications of Liu and Singh's proposals. The test statistic is shown to be asymptotically normal when k  = 2, and compares favorably with Liu and Singh (2006) if the underlying distributions are either symmetric with light tails or asymmetric. In the case of skewed distributions considered in this paper the power of the proposed tests can attain twice the power of the Liu‐Singh test for d  ≥ 1. Finally, in the k ‐sample case, it is shown that the asymptotic distribution of the proposed percentile modified Kruskal‐Wallis type test is χ 2 with k  − 1 degrees of freedom. Power properties of this k ‐sample test are similar to those for the proposed two sample one. The Canadian Journal of Statistics 39: 356–369; 2011 © 2011 Statistical Society of Canada

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here