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Nonparametric hypothesis testing for equality of means on the simplex

Tsagris, Michail; Preston, Simon P.; Wood, Andrew T.A.

Authors

Michail Tsagris

SIMON PRESTON simon.preston@nottingham.ac.uk
Professor of Statistics and Applied Mathematics

Andrew T.A. Wood



Abstract

In the context of data that lie on the simplex, we investigate use of empirical and exponential empirical likelihood, and Hotelling and James statistics, to test the null hypothesis of equal population means based on two independent samples. We perform an extensive numerical study using data simulated from various distributions on the simplex. The results, taken together with practical considerations regarding implementation, support the use of bootstrap-calibrated James statistic.

Citation

Tsagris, M., Preston, S. P., & Wood, A. T. (in press). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2), https://doi.org/10.1080/00949655.2016.1216554

Journal Article Type Article
Acceptance Date Jul 19, 2016
Online Publication Date Aug 2, 2016
Deposit Date Jun 30, 2017
Publicly Available Date Mar 29, 2024
Journal Journal of Statistical Computation and Simulation
Print ISSN 0094-9655
Electronic ISSN 1563-5163
Publisher Taylor & Francis Open
Peer Reviewed Peer Reviewed
Volume 87
Issue 2
DOI https://doi.org/10.1080/00949655.2016.1216554
Keywords Compositional data, hypothesis testing, Hotelling test, James test, nonparametric, empirical likelihood, bootstrap
Public URL https://nottingham-repository.worktribe.com/output/806922
Publisher URL http://www.tandfonline.com/doi/abs/10.1080/00949655.2016.1216554
Additional Information This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistical Computation and Simulation on 02 August 2016, available online: http://www.tandfonline.com/10.1080/00949655.2016.1216554

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