Nonparametric hypothesis testing for equality of means on the simplex

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Tsagris, Michail, Preston, Simon P. and Wood, Andrew T.A. (2016) Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87 (2). pp. 406-422. ISSN 1563-5163

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/806922
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
Keywords: Compositional data, hypothesis testing, Hotelling test, James test, nonparametric, empirical likelihood, bootstrap
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: https://doi.org/10.1080/00949655.2016.1216554
Depositing User: Preston, Simon
Date Deposited: 30 Jun 2017 09:29
Last Modified: 04 May 2020 18:08
URI: https://eprints.nottingham.ac.uk/id/eprint/43849

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