JOURNAL ARTICLE

New nonparametric tests based on data depth for multivariate multi-sample location problem

D. T. ShirkeSwapnil Dattatray Khorate

Year: 2023 Journal:   Communications in Statistics - Simulation and Computation Vol: 53 (12)Pages: 5764-5779   Publisher: Taylor & Francis

Abstract

Data depth based nonparametric tests for multivariate multisample location problem are provided which extend the depth based nonparametric test for multivariate two-sample location problem by Shirke and Khorate (2018) [Shirke, D.T. and Khorate, S.D., 2018. Two-sample nonparametric test for testing equality of locations based on data depth. Journal of the Indian Society for Probability and Statistics, 19, pp. 9-23.] to the multi-sample setting. Proposed tests are based on the correlations among the depths of data points. Power comparison of proposed tests with the existing depth based nonparametric tests is provided using a simulation study based on a permutation test. Simulation study reveals that the proposed tests give comparable powers compared to the existing data depth based nonparametric tests. Proposed tests are illustrated with real life data sets.

Keywords:
Nonparametric statistics Multivariate statistics Sample (material) Statistics Goldfeld–Quandt test Mathematics Permutation (music) Statistical hypothesis testing Multivariate analysis Test statistic Z-test

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Citation History

Topics

Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Distribution Estimation and Applications
Physical Sciences →  Mathematics →  Statistics and Probability
Advanced Statistical Process Monitoring
Social Sciences →  Decision Sciences →  Statistics, Probability and Uncertainty

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