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Non Parametric Prediction in Stationary Processes

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Book cover Specifying Statistical Models

Part of the book series: Lecture Notes in Statistics ((LNS,volume 16))

Abstract

We present a class of non parametric predictions and study their asymptotic properties. The general framework of the study allows us to predict the distribution of the nonobserved variable. We give also the results of some simulations carried out in an elementary case.

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Bibliography

  1. D. Bosq — Une méthode non paramétrique de prédiction d’un processus stationnaire. Prédiction d’une mesure aléatoire. CRAS, A, t. 290, p. 711–713 (1980).

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  2. D. Bosq — Sur la prédiction non paramétrique de variables aléatoires et de mesures aléatoires. Publ. Interne — U.E.R. de Maths. Pures et Appl. Lille I — n° 164 (1979).

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  3. G. Collomb — Convergence du prédictogramme en prédiction non paramétrique. (In this volume).

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  4. J.L. Gastwirth — H. Rubin — The asymptotic distribution theory of the empiric C.D.F. for mixing stochastic processes. Annals of Stat. Vol. 3 n° 4 p. 800–824 (1975).

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  5. C. Guilbart — Etude des produits scalaires sur l’espace des mesures. Annales de l’I.H.P. (1979).

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  6. R. Kalaidjian — Ebauche d’une étude comparée sur les efficacités de certaines méthodes de prédiction pour un ARMA perturbé “Statistique et Analyse des données”). (1982).

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Author information

Authors and Affiliations

  1. University of Lille I, France

    Denis Bosq

Authors
  1. Denis Bosq
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Editor information

Editors and Affiliations

  1. Université d’Aix-Marseille II, France

    J. P. Florens

  2. C.O.R.E., Université Catholique de Louvain, Belgium

    M. Mouchart

  3. Université de Rouen, France

    J. P. Raoult

  4. Facultés Universitaires Saint-Louis, Bruxelles, Belgium

    L. Simar

  5. University of Nottingham, UK

    A. F. M. Smith

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© 1983 Springer-Verlag New York Inc.

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Bosq, D. (1983). Non Parametric Prediction in Stationary Processes. In: Florens, J.P., Mouchart, M., Raoult, J.P., Simar, L., Smith, A.F.M. (eds) Specifying Statistical Models. Lecture Notes in Statistics, vol 16. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-5503-1_5

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  • DOI: https://doi.org/10.1007/978-1-4612-5503-1_5

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-90809-0

  • Online ISBN: 978-1-4612-5503-1

  • eBook Packages: Springer Book Archive

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