An estimation method for the chi-square divergence with application to test of hypotheses
| Autor: | Broniatowski, Michel, Leorato, Samantha |
|---|---|
| Přispěvatelé: | Laboratoire de Statistique Théorique et Appliquée (LSTA), Université Pierre et Marie Curie - Paris 6 (UPMC), Dipartimento di Studi Economico-Finanziari e Metodi Quantitativi (SEFeMeQ), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Progetto Ateneo di Padova coordinated by Prof. G. Celant., Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Hypothesis testing
Linear constraints Contamination models Chi-square divergence [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] FOS: Mathematics Fenchel-Legendre transform Marginal distributions Mathematics - Statistics Theory Statistics Theory (math.ST) Inliers [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH] ASM (2010) 62F03 62F10 62F30 |
| Zdroj: | Journal of Multivariate Analysis Journal of Multivariate Analysis, Elsevier, 2016, 97 (6), pp.409-1436 Journal of Multivariate Analysis, 2016, 97 (6), pp.409-1436 |
| ISSN: | 0047-259X 1095-7243 |
| Popis: | We propose a new definition of the chi-square divergence between distributions. Based on convexity properties and duality, this version of the {\chi}^2 is well suited both for the classical applications of the {\chi}^2 for the analysis of contingency tables and for the statistical tests for parametric models, for which it has been advocated to be robust against inliers. We present two applications in testing. In the first one we deal with tests for finite and infinite numbers of linear constraints, while, in the second one, we apply {\chi}^2-methodology for parametric testing against contamination. |
| Databáze: | OpenAIRE |
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