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<p>Hypothesis testing can be applied in a detective fashion in the field of data science. Different tests are developed to test the population parameters. This article provides a data depth-based test for testing the equality of location vectors of the two multivariate populations. The data depth-based outlyingness function is used to define the test statistics. The performance in terms of power of the proposed test is compared with some available data depth-based tests for testing the equality of location vectors. A permutation procedure is used to obtain the <i>P</i> value of the test. The proposed test does not assume any distributional assumption. An empirical power comparison shows that the proposed test outperforms in most of the cases. The applicability of the proposed test is illustrated with the help of real data.</p>

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Two-Sample Test for Testing Equality of Location Vectors Based on Outlying Function

  • 期刊论文

  • 发表日期：

    2025年2月11日

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  • M. S. Barale,
  • D. T. Shirke

摘要

Hypothesis testing can be applied in a detective fashion in the field of data science. Different tests are developed to test the population parameters. This article provides a data depth-based test for testing the equality of location vectors of the two multivariate populations. The data depth-based outlyingness function is used to define the test statistics. The performance in terms of power of the proposed test is compared with some available data depth-based tests for testing the equality of location vectors. A permutation procedure is used to obtain the P value of the test. The proposed test does not assume any distributional assumption. An empirical power comparison shows that the proposed test outperforms in most of the cases. The applicability of the proposed test is illustrated with the help of real data.