IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/72771.html
   My bibliography  Save this paper

Nonparametric hypothesis testing for equality of means on the simplex

Author

Listed:
  • Tsagris, Michail
  • Preston, Simon
  • T.A. Wood, Andrew

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.

Suggested Citation

  • Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Nonparametric hypothesis testing for equality of means on the simplex," MPRA Paper 72771, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:72771
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/72771/1/MPRA_paper_72771.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simon P. Preston & Andrew T. A. Wood, 2010. "Two‐Sample Bootstrap Hypothesis Tests for Three‐Dimensional Labelled Landmark Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(4), pages 568-587, December.
    2. T. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2011. "A data-based power transformation for compositional data," MPRA Paper 53068, University Library of Munich, Germany.
    3. Jing, Bing-Yi, 1995. "Two-sample empirical likelihood method," Statistics & Probability Letters, Elsevier, vol. 24(4), pages 315-319, September.
    4. Jane Fry & Tim Fry & Keith McLaren, 2000. "Compositional data analysis and zeros in micro data," Applied Economics, Taylor & Francis Journals, vol. 32(8), pages 953-959.
    5. Paulo Rodrigues & Ana Lima, 2009. "Analysis of an European union election using principal component analysis," Statistical Papers, Springer, vol. 50(4), pages 895-904, August.
    6. Liu, Yukun & Zou, Changliang & Zhang, Runchu, 2008. "Empirical likelihood for the two-sample mean problem," Statistics & Probability Letters, Elsevier, vol. 78(5), pages 548-556, April.
    7. Krishnamoorthy, K. & Yu, Jianqi, 2004. "Modified Nel and Van der Merwe test for the multivariate Behrens-Fisher problem," Statistics & Probability Letters, Elsevier, vol. 66(2), pages 161-169, January.
    8. Getulio J. A. Amaral & Andrew T. A. Wood, 2010. "Empirical likelihood methods for two-dimensional shape analysis," Biometrika, Biometrika Trust, vol. 97(3), pages 757-764.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Philippos Louis & Orestis Troumpounis & Nikolaos Tsakas & Dimitrios Xefteris, 2020. "Protest voting in the laboratory," "Marco Fanno" Working Papers 0247, Dipartimento di Scienze Economiche "Marco Fanno".

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.
    2. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.
    3. Tsao, Min & Wu, Fan, 2015. "Two-sample extended empirical likelihood for estimating equations," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 1-15.
    4. N. Balakrishnan & N. Martín & L. Pardo, 2017. "Empirical phi-divergence test statistics for the difference of means of two populations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(2), pages 199-226, April.
    5. Wu, Fan & Tsao, Min, 2014. "Two-sample extended empirical likelihood," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 81-87.
    6. Quynh Van Nong & Chi Tim Ng, 2021. "Clustering of subsample means based on pairwise L1 regularized empirical likelihood," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 135-174, February.
    7. Varron, Davit, 2016. "Empirical likelihood confidence tubes for functional parameters in plug-in estimation," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 100-118.
    8. Tsagris, Michail, 2014. "The k-NN algorithm for compositional data: a revised approach with and without zero values present," MPRA Paper 65866, University Library of Munich, Germany.
    9. Liu, Yukun & Yu, Chi Wai, 2010. "Bartlett correctable two-sample adjusted empirical likelihood," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1701-1711, August.
    10. Shen, Junshan & Yuen, Kam Chuen & Liu, Chunling, 2016. "Empirical likelihood confidence regions for one- or two- samples with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 285-293.
    11. S. H. Lin & R. S. Wang, 2009. "Inferences on a linear combination of K multivariate normal mean vectors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(4), pages 415-428.
    12. Xu, Li-Wen, 2015. "Parametric bootstrap approaches for two-way MANOVA with unequal cell sizes and unequal cell covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 291-303.
    13. Mardia, Kanti V. & Wiechers, Henrik & Eltzner, Benjamin & Huckemann, Stephan F., 2022. "Principal component analysis and clustering on manifolds," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    14. McKeague, Ian W. & Zhao, Yichuan, 2002. "Simultaneous confidence bands for ratios of survival functions via empirical likelihood," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 405-415, December.
    15. Chai, Andreas & Stepanova, Elena & Moneta, Alessio, 2023. "Quantifying expenditure hierarchies and the expansion of global consumption diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 860-886.
    16. Jack Gregory & David I. Stern, 2012. "Fuel Choices in Rural Maharashtra," CCEP Working Papers 1207, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    17. Zou, Changliang & Liu, Yukun & Qin, Peng & Wang, Zhaojun, 2007. "Empirical likelihood ratio test for the change-point problem," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 374-382, February.
    18. Apratim Guha & Atanu Biswas & Abhik Ghosh, 2021. "A nonparametric two‐sample test using a general φ‐divergence‐based mutual information," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(2), pages 180-202, May.
    19. Margaret A. Abernethy & Jan Bouwens & Laurence Van Lent, 2013. "The Role of Performance Measures in the Intertemporal Decisions of Business Unit Managers," Contemporary Accounting Research, John Wiley & Sons, vol. 30(3), pages 925-961, September.
    20. Ivan Zezula, 2009. "Implementation of a new solution to the multivariate Behrens-Fisher problem," Stata Journal, StataCorp LP, vol. 9(4), pages 593-598, December.

    More about this item

    Keywords

    Compositional data; hypothesis testing; Hotelling test; James test; non parametric; empirical likelihood; bootstrap;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:72771. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.