Please use this identifier to cite or link to this item: https://doi.org/10.1080/00949650802260071
Title: Bandwidth selection through cross-validation for semi-parametric varying-coefficient partially linear models
Authors: Li, J. 
Palta, M.
Keywords: Cross-validation
Generalized cross-validation
Partially linear model
Semi-parametric model
Varying-coefficient model
Issue Date: Nov-2009
Citation: Li, J., Palta, M. (2009-11). Bandwidth selection through cross-validation for semi-parametric varying-coefficient partially linear models. Journal of Statistical Computation and Simulation 79 (11) : 1277-1286. ScholarBank@NUS Repository. https://doi.org/10.1080/00949650802260071
Abstract: We study bandwidth selection for a class of semi-parametric models. The proper choice of optimal bandwidth minimizes the prediction errors of the model. We provide detailed derivation of our procedure and the corresponding computation algorithms. Our proposed method simplifies the computation of the cross-validation criteria and facilitates more complicated inference and analysis in practice. A data set from Wisconsin Diabetes Registry has been analysed as an illustration. © 2009 Taylor & Francis.
Source Title: Journal of Statistical Computation and Simulation
URI: http://scholarbank.nus.edu.sg/handle/10635/105035
ISSN: 00949655
DOI: 10.1080/00949650802260071
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