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Tests non paramétriques optimaux pour une autorégression d'ordre un


  • Marc Hallin
  • Jean-Marie Dufour


Ce Texte Developpe des Methodes D'inference Non Parametriques Pour le Processus Autoregressif D'ordre Un. le Probleme Etudie Est de Tester N'importe Quelle Hypothese Affirmant Que le Coefficient D'autocorrelation (...) a une Valeur Donnee (...) Ou (...) Est une Valeur Admissible Arbitraire (...). Nous Considerons la Famille des Tests Bases Sur les Autocorrelations de Rangs du Modele Transforme Sour (...). Ces Tests Sont Applicables (...) Sous la Simple Condition Que les Innovations de Processus Sont I.I.D. Continues. Dans la Classe Consideree, Nous Derivons des Tests Asymptotiquement Optimaux de (...) Pour des Contre Hypotheses Locales, Unilaterales Ou Bilaterales. Nous Donnons la Distribution Asymptotique des Tests Sous L'hypothese Nulle Ainsi Que Pour des Suites D'hypotheses Contigues, et Calculons Leur Efficacite Asymptotique Relative Par Rapport a Plusieurs Procedures Disponibles (Parametriques et Non Parametriques) Pour Tester les Memes Hypotheses. la Possibilite de Rendre les Tests Exacts Par Enumeration Ou Simulation Est Aussi Examinee.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Marc Hallin & Jean-Marie Dufour, 1987. "Tests non paramétriques optimaux pour une autorégression d'ordre un," ULB Institutional Repository 2013/2011, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:ulb:ulbeco:2013/2011

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