Efficient estimation for semivarying-coefficient models

Xia, YC and Zhang, W.Y. and Tong, H. (2004) Efficient estimation for semivarying-coefficient models. Biometrika, 91 (3). pp. 661-681. ISSN 0006-3444. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1093/biomet/91.3.661

Abstract

Motivated by two practical problems, we propose a new procedure for estimating a semivarying-coefficient model. Asymptotic properties are established which show that the bias of the parameter estimator is of order h(3) when a symmetric kernel is used, where h is the bandwidth, and the variance is of order n(-1) and efficient in the semiparametric sense. Undersmoothing is unnecessary for the root-n consistency of the estimators. Therefore, commonly used bandwidth selection methods can be employed. A model selection method is also developed. Simulations demonstrate how the proposed method works. Some insights are obtained into the two motivating problems by using the proposed models.

Item Type: Article
Uncontrolled keywords: efficient estimator; local linear; semivarying-coefficient model; strong alpha-mixing; varying-coefficient model
Subjects: H Social Sciences > HA Statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Depositing User: Judith Broom
Date Deposited: 19 Dec 2007 18:22
Last Modified: 14 Jan 2010 13:59
Resource URI: http://kar.kent.ac.uk/id/eprint/601 (The current URI for this page, for reference purposes)
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