Two-sample test for sparse high-dimensional multinomial distributions

• Amanda Plunkett ^[2] ; Junyong Park ^[1]
  1. [1] University of Maryland, College Park

     University of Maryland, College Park

     Estados Unidos

     
  2. [2] Department of Defense
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 28, Nº. 3, 2019, págs. 804-826
• Idioma: inglés
• DOI: 10.1007/s11749-018-0600-8
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• Resumen

  • In this paper we consider testing the equality of probability vectors of two independent multinomial distributions in high dimension. The classical Chi-square test may have some drawbacks in this case since many of cell counts may be zero or may not be large enough. We propose a new test and show its asymptotic normality and the asymptotic power function. Based on the asymptotic power function, we present an application of our result to a neighborhood-type test which has been previously studied, especially for the case of fairly small p values. To compare the proposed test with existing tests, we provide numerical studies including simulations and real data examples