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Original Articles

Nonparametric tests for multivariate locations based on data depth

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Pages 753-776 | Received 01 Jun 2016, Accepted 17 Oct 2017, Published online: 06 Dec 2017
 

ABSTRACT

The present paper deals with the problem of testing equality of locations of two multivariate distributions using a notion of data depth. A notion of data depth has been used to measure centrality/outlyingness of a given point in a given data cloud. The paper proposes two nonparametric tests for testing equality of locations of two multivariate populations which are developed by observing the behavior of the depth versus depth plot. Simulation study reveals that the proposed tests are superior to the existing tests based on the data depth with regard to power. Illustrations with real data are provided.

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Acknowledgment

Authors would like to thank reviewers for their valuable comments and suggestions to improve the quality of the paper. This work is supported by the University Grants Commission New Delhi (INDIA) under innovative program- Teaching and Research in Interdisciplinary and Emerging Area and University Grants Commission New Delhi (INDIA) under Special Assistance Program (SAP) sanctioned to Department of Statistics, Shivaji University, Kolhapur (INDIA).

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