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论文类型：期刊论文

发表时间：2010-09-01

发表刊物：STATISTICS & PROBABILITY LETTERS

收录刊物：SCIE、Scopus

卷号：80

期号：17-18

页面范围：1271-1283

ISSN号：0167-7152

关键字：Semiparametric model; Consistency; Convergence rate; Asymptotic normality; Empirical process method

摘要：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.