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Indexed by:期刊论文

Date of Publication:2010-09-01

Journal:STATISTICS & PROBABILITY LETTERS

Included Journals:SCIE、Scopus

Volume:80

Issue:17-18

Page Number:1271-1283

ISSN No.:0167-7152

Key Words:Semiparametric model; Consistency; Convergence rate; Asymptotic normality; Empirical process method

Abstract:This paper considers a partially nonlinear model E(Y vertical bar X, T) = H(beta(T)X) g(T), which is a sub-model of the general partially nonlinear model but has some particular advantages in statistical inference. We develop a sieve least squares method to estimate the parameters of the parametric part and the nonparametric part. The consistency and asymptotic normality of the estimator for the parametric part are established. Simulation results show that the sieve estimators perform quite well. (C) 2010 Elsevier B.V. All rights reserved.