Local polynomial fitting in semivarying coefficient models

Zhang, Wenyang and Lee, Sik-Yum and Song, Xin-Yuan (2002) Local polynomial fitting in semivarying coefficient models. Journal of Multivariate Analysis, 82 (1). pp. 166-188. ISSN 0047-259X . (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Varying coefficient models are useful extensions of the classical linear models. Under the condition that the coefficient functions possess about the same degrees of smoothness, the model can easily be estimated via simple local regression.. This leads to the one-step estimation procedure. In this paper, we consider a semivarying coefficient model which is an extension of the varying coefficient model, which is called the semivarying-coefficient model. Procedures for estimation of the linear part and the nonparametric part are developed and their associated statistical properties are studied. The proposed methods are illustrated by some simulation studies and a real example.

Item Type: Article
Uncontrolled keywords: semivarying-coefficient models; varying-coefficient; models local polynomial fit; one-step method; two-step method; optimal rate of convergence; mean squared errors
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 25 Oct 2008 17:57
Last Modified: 25 Apr 2014 12:06
Resource URI: https://kar.kent.ac.uk/id/eprint/10598 (The current URI for this page, for reference purposes)
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