Nonparametric tests for multivariate multi-sample locations based on data depth

被引：9
|
作者：
Pawar, Somanath D. [1 ]
Shirke, Digambar T. [1 ]
机构：
[1] Shivaji Univ, Dept Stat, Kolhapur, Maharashtra, India
来源：
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2019年 / 89卷 / 09期
关键词：
Data depth; multivariate nonparametric tests; permutation tests; PERMUTATION TESTS; RANK-TESTS; EQUALITY; NOTION;
D O I：
10.1080/00949655.2019.1590577
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Several nonparametric tests for multivariate multi-sample location problem are proposed in this paper. These tests are based on the notion of data depth, which is used to measure the centrality/outlyingness of a given point with respect to a given distribution or a data cloud. Proposed tests are completely nonparametric and implemented through the idea of permutation tests. Performance of the proposed tests is compared with existing parametric test and nonparametric test based on data depth. An extensive simulation study reveals that proposed tests are superior to the existing tests based on data depth with regard to power. Illustrations with real data are provided.
引用
收藏
页码：1574 / 1591
页数：18
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