Non parametric estimation of the regression operator

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Details

In this work, we are interested in the functional non parametric estimation using the k nearest neighbors method (k-NN) for a scalar response variable given a random variable taking values in a semi metric space. In the first part, we will explain how this method work (with their algorithm) by giving some concepts that help us to better understand the basic idea of the k-NN method. Then, and using these concepts, we will give the asymptotic properties for real data, vector data and functional data. In the last, we give more fields for the application of this method and giving some simulation examples to compare the kNN method and the parametric and non parametric methods.

Autorentext

I am working at Tahar Moulay University of Saida, Algeria and Member at Stochastic Models, Statistics and Applications Laboratory. My research area is mathematical statistics. My specific field of research is the Statistics in infinite dimension, also statistics of stochastic processes.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786200506993
    • Sprache Englisch
    • Größe H220mm x B150mm x T8mm
    • Jahr 2020
    • EAN 9786200506993
    • Format Kartonierter Einband
    • ISBN 620050699X
    • Veröffentlichung 13.01.2020
    • Titel Non parametric estimation of the regression operator
    • Autor Fethi Madani
    • Untertitel The k-nearest neighbors approach
    • Gewicht 197g
    • Herausgeber LAP LAMBERT Academic Publishing
    • Anzahl Seiten 120
    • Genre Mathematik

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