Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/91.3.661
Title: Efficient estimation for semivarying-coefficient models
Authors: Xia, Y. 
Zhang, W.
Tong, H.
Keywords: Efficient estimator
Local linear
Semivarying-coefficient model
Strong α-mixing
Varying-coefficient model
Issue Date: 2004
Citation: Xia, Y., Zhang, W., Tong, H. (2004). Efficient estimation for semivarying-coefficient models. Biometrika 91 (3) : 661-681. ScholarBank@NUS Repository. https://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 h3 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. © 2004 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105110
ISSN: 00063444
DOI: 10.1093/biomet/91.3.661
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