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https://doi.org/10.1080/10485252.2010.533768
Title: | Optimal zone for bandwidth selection in semiparametric models | Authors: | Li, J. Zhang, W. Wu, Z. |
Keywords: | Asymptotic mean square error Cross-validation Neumann series approximation Optimal bandwidth Taylor series expansion |
Issue Date: | Sep-2011 | Citation: | Li, J., Zhang, W., Wu, Z. (2011-09). Optimal zone for bandwidth selection in semiparametric models. Journal of Nonparametric Statistics 23 (3) : 701-717. ScholarBank@NUS Repository. https://doi.org/10.1080/10485252.2010.533768 | Abstract: | We study the general problem of bandwidth selection in semiparametric regression. By expanding the higher-order terms in the Taylor series for the asymptotic mean-squared error, we provide a theoretical justification for the earlier empirical observations of an optimal zone of bandwidths in the literature. Based on the idea of cross-validating parametrical estimates, we further introduce a novel bandwidth selector for semiparametric models. The method is demonstrated by numerical studies to be able to preserve the selected bandwidth within the optimal zone. This data-driven cross-validation method may also be applicable for model diagnosis and longitudinal data settings. Examples from two clinical trials are provided to illustrate the applications. © American Statistical Association and Taylor & Francis 2011. | Source Title: | Journal of Nonparametric Statistics | URI: | http://scholarbank.nus.edu.sg/handle/10635/105288 | ISSN: | 10485252 | DOI: | 10.1080/10485252.2010.533768 |
Appears in Collections: | Staff Publications |
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