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Two-stage model selection procedures in partially linear regression
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Journal Article
Two-stage model selection procedures in partially linear regression
2004
Overview
The authors propose a two-stage estimation procedure for the partially linear model Y=f0(T)+X′β0+ε . They show how to estimate consistently the location of the nonzero components of β0. Their approach turns out to be compatible with minimax adaptive estimation of f0over Besov balls in the case of penalized least squares. Their proofs are based on a new type of oracle inequality. /// Les auteurs proposent une procédure d'estimation en deux temps pour le modèle partiellement linéaire Y=f0(T)+X′β0+ε . Ils montrent comment estimer de façon convergente la position des composantes non nulles de β0. Leur approche s'avère compatible avec l'estimation minimax adaptative de f0sur les boules de Besov dans le cas des moindres carrés pénalisés. Leurs démonstrations s'appuient sur une inégalité d'oracle d'un nouveau genre.
Publisher
Wiley-Blackwell,Statistical Society of Canada,Wiley‐Blackwell,Wiley Subscription Services, Inc
Subject
