Projection-Type Estimation for Varying Coefficient Regression Models


Lee, Young K. ; Mammen, Enno ; Park, Byeong U.



DOI: https://doi.org/10.3150/10-BEJ331
URL: http://projecteuclid.org/euclid.bj/1327068622
Additional URL: http://arxiv.org/pdf/1203.0403.pdf
Document Type: Article
Year of publication: 2012
The title of a journal, publication series: Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability
Volume: 18
Issue number: 1
Page range: 177-205
Place of publication: The Hague
Publishing house: Bernoulli Soc. for Mathematical Statistics and Probability
ISSN: 1350-7265
Publication language: English
Institution: Außerfakultäre Einrichtungen > SFB 884
Subject: 330 Economics
Abstract: In this paper we introduce new estimators of the coefficient functions in the varying coefficient regression model. The proposed estimators are obtained by projecting the vector of the full-dimensional kernel-weighted local polynomial estimators of the coefficient functions onto a Hilbert space with a suitable norm. We provide a backfitting algorithm to compute the estimators. We show that the algorithm converges at a geometric rate under weak conditions. We derive the asymptotic distributions of the estimators and show that the estimators have the oracle properties. This is done for the general order of local polynomial fitting and for the estimation of the derivatives of the coefficient functions, as well as the coefficient functions themselves. The estimators turn out to have several theoretical and numerical advantages over the marginal integration estimators studied by Yang, Park, Xue and Härdle [J. Amer. Statist. Assoc. 101 (2006) 1212–1227].

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Lee, Young K. ; Mammen, Enno ; Park, Byeong U. (2012) Projection-Type Estimation for Varying Coefficient Regression Models. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability The Hague 18 1 177-205 [Article]


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