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Simplicial bivariate tests for randomness

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  • Van Bever, Germain

Abstract

This paper introduces a simplex-based extension of the concept of runs to the bivariate setup which allows to test for randomness under the null hypothesis of angularly symmetric distributions. The statistic’s null limiting distribution is derived and Monte Carlo studies evaluate the test performances.

Suggested Citation

  • Van Bever, Germain, 2016. "Simplicial bivariate tests for randomness," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 20-25.
    • Handle: RePEc:eee:stapro:v:112:y:2016:i:c:p:20-25
    DOI: 10.1016/j.spl.2016.01.013
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    References listed on IDEAS

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    1. Taskinen, Sara & Oja, Hannu & Randles, Ronald H., 2005. "Multivariate Nonparametric Tests of Independence," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 916-925, September.
    2. Paindaveine, Davy, 2009. "On Multivariate Runs Tests for Randomness," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1525-1538.
    3. Rainer Dyckerhoff & Christophe Ley & Davy Paindaveine, 2015. "Depth-based runs tests for bivariate central symmetry," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(5), pages 917-941, October.
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    Cited by:

    1. Ilija Tanackov & Feta Sinani & Miomir Stanković & Vuk Bogdanović & Željko Stević & Mladen Vidić & Jelena Mihaljev-Martinov, 2019. "Natural Test for Random Numbers Generator Based on Exponential Distribution," Mathematics, MDPI, vol. 7(10), pages 1-14, October.

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