Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 6 (2012), 760-782.
A nonparametric multivariate multisample test based on data depth
Shojaeddin Chenouri and Christopher G. Small
Full-text: Open access
Abstract
In this paper, we construct a family of nonparametric multivariate multisample tests based on depth rankings. These tests are of Kruskal-Wallis type in the sense that the samples are variously ordered. However, unlike the Kruskal-Wallis test, these tests are based upon a depth ranking using a statistical depth function such as the halfspace depth or the Mahalanobis depth, etc. The types of tests we propose are adapted to the depth function that is most appropriate for the application. Under the null hypothesis that all samples come from the same distribution, we show that the test statistic asymptotically has a chi-square distribution. Some comparisons of power are made with the Hotelling T2, and the test of Choi and Marden (1997). Our test is particularly recommended when the data are of unknown distribution type where there is some evidence that the density contours are not elliptical. However, when the data are normally distributed, we often obtain high relative power.
Article information
Source
Electron. J. Statist., Volume 6 (2012), 760-782.
Dates
First available in Project Euclid: 9 May 2012
Permanent link to this document
https://projecteuclid.org/euclid.ejs/1336568105
Digital Object Identifier
doi:10.1214/12-EJS692
Mathematical Reviews number (MathSciNet)
MR2988428
Zentralblatt MATH identifier
1336.62138
Keywords
Data depth multivariate nonparametric tests Kruskal-Wallis test depth-depth plot
Citation
Chenouri, Shojaeddin; Small, Christopher G. A nonparametric multivariate multisample test based on data depth. Electron. J. Statist. 6 (2012), 760--782. doi:10.1214/12-EJS692. https://projecteuclid.org/euclid.ejs/1336568105
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