Abbreviated Journal Title
Ann. Stat.
Keywords
series estimation method; partially linear; varying coefficient; asymptotic normality; semiparametric efficiency; GENERALIZED CROSS-VALIDATION; REGRESSION-MODELS; ASYMPTOTIC NORMALITY; LOCAL ASYMPTOTICS; SERIES ESTIMATORS; LONGITUDINAL DATA; CP; Statistics & Probability
Abstract
In this paper we propose a general series method to estimate a semiparametric partially linear varying coefficient model. We establish the consistency and root n-normality property of the estimator of the finite-dimensional parameters of the model, We further show that, when the error is conditionally homoskedastic. this estimator is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator of the finite-dimensional parameter reaches the semiparametric efficiency bound of this model. A small-scale simulation is reported to examine the finite.sample performance of the proposed estimator, and an empirical application is presented to illustrate the usefulness of the proposed method in practice. We also discuss how to obtain an efficient estimation result when the error is conditional heteroskedastic.
Journal Title
Annals of Statistics
Volume
33
Issue/Number
1
Publication Date
1-1-2005
Document Type
Article
Language
English
First Page
258
Last Page
283
WOS Identifier
ISSN
0090-5364
Recommended Citation
Ahmad, Ibrahim; Leelahanon, Sittisak; and Li, Qi, "Efficient estimation of a semiparametric partially linear varying coefficient model" (2005). Faculty Bibliography 2000s. 4942.
https://stars.library.ucf.edu/facultybib2000/4942
Comments
Authors: contact us about adding a copy of your work at STARS@ucf.edu