Michail Tsagris
Nonparametric hypothesis testing for equality of means on the simplex
Tsagris, Michail; Preston, Simon P.; Wood, Andrew T.A.
Authors
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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