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Un test d'adéquation global pour la fonction de répartition conditionnelle

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Title: Un test d'adéquation global pour la fonction de répartition conditionnelle
Alternate Title: A global test of goodness-of-fit for the conditional distribution function
Authors: Ferrigno, Sandie1 ferrigno@math.univ-montp2.fr, Ducharme, Gilles R.1 ducharme@math.univ-montp2.fr
Source: Comptes Rendus. Mathématique. Sep2005, Vol. 341 Issue 5, p313-316. 4p.
Subjects: Goodness-of-fit tests, Mathematical models, Statistical hypothesis testing, Statistics, Distribution (Probability theory), Asymptotic distribution
Abstract (English): Abstract: We propose a global test of goodness-of-fit to assess the validity of an entertained statistical model by testing simultaneously all the assumptions made about it. This test is based on a local polynomial estimator of the conditional distribution function and on the standard paradigm relating the distance between the nonparametric estimator and the theoretical parametric model. We derive the asymptotic distribution of the resulting test statistic under both the null hypothesis and local alternatives. To cite this article: S. Ferrigno, G.R. Ducharme, C. R. Acad. Sci. Paris, Ser. I 341 (2005). [Copyright &y& Elsevier]
Abstract (French): Résumé: Nous proposons un test d''''adéquation global permettant de juger de la validité d''''un modèle statistique en testant simultanément toutes les suppositions sous-jacentes à celui-ci. Ce test est basé sur l''''estimateur polynomial local de la fonction de répartition conditionnelle et sur un paradigme standard qui mesure la distance entre cet estimateur non paramétrique et le modèle paramétrique théorique. Nous obtenons le comportement asymptotique de la statistique du test à la fois sous l''''hypothèse nulle et sous des alternatives locales. Pour citer cet article : S. Ferrigno, G.R. Ducharme, C. R. Acad. Sci. Paris, Ser. I 341 (2005).
Copyright of Comptes Rendus. Mathématique is the property of Academie des Science, Centre Mersenne and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Un test d'adéquation global pour la fonction de répartition conditionnelle
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  Data: A global test of goodness-of-fit for the conditional distribution function
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  Data: <searchLink fieldCode="AR" term="%22Ferrigno%2C+Sandie%22">Ferrigno, Sandie</searchLink><relatesTo>1</relatesTo><i> ferrigno@math.univ-montp2.fr</i><br /><searchLink fieldCode="AR" term="%22Ducharme%2C+Gilles+R%2E%22">Ducharme, Gilles R.</searchLink><relatesTo>1</relatesTo><i> ducharme@math.univ-montp2.fr</i>
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  Data: <searchLink fieldCode="DE" term="%22Goodness-of-fit+tests%22">Goodness-of-fit tests</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+hypothesis+testing%22">Statistical hypothesis testing</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Asymptotic+distribution%22">Asymptotic distribution</searchLink>
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  Data: Abstract: We propose a global test of goodness-of-fit to assess the validity of an entertained statistical model by testing simultaneously all the assumptions made about it. This test is based on a local polynomial estimator of the conditional distribution function and on the standard paradigm relating the distance between the nonparametric estimator and the theoretical parametric model. We derive the asymptotic distribution of the resulting test statistic under both the null hypothesis and local alternatives. To cite this article: S. Ferrigno, G.R. Ducharme, C. R. Acad. Sci. Paris, Ser. I 341 (2005). [Copyright &y& Elsevier]
– Name: Abstract
  Label: Abstract (French)
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  Data: Résumé: Nous proposons un test d''''adéquation global permettant de juger de la validité d''''un modèle statistique en testant simultanément toutes les suppositions sous-jacentes à celui-ci. Ce test est basé sur l''''estimateur polynomial local de la fonction de répartition conditionnelle et sur un paradigme standard qui mesure la distance entre cet estimateur non paramétrique et le modèle paramétrique théorique. Nous obtenons le comportement asymptotique de la statistique du test à la fois sous l''''hypothèse nulle et sous des alternatives locales. Pour citer cet article : S. Ferrigno, G.R. Ducharme, C. R. Acad. Sci. Paris, Ser. I 341 (2005). </ce:abst [Copyright 2005 Elsevier]
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  Data: <i>Copyright of Comptes Rendus. Mathématique is the property of Academie des Science, Centre Mersenne and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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