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|Title:||Adaptive semi-varying coefficient model selection||Authors:||Hu, T.
Semi-varying coefficient model
|Issue Date:||Apr-2012||Citation:||Hu, T., Xia, Y. (2012-04). Adaptive semi-varying coefficient model selection. Statistica Sinica 22 (2) : 575-599. ScholarBank@NUS Repository. https://doi.org/10.5705/ss.2010.105||Abstract:||Identification of constant coefficients in a semi-varying coefficient model is an important issue (Zhang et al (2002)). We propose a novel method for this by combining local polynomial smoothing (Fan and Zhang (1999)) with shrinkage estimation (Tibshirani (1996)). Unlike the stepwise procedure (Xia, Zhang, and Tong (2004)), our method can identify the constant coefficients and estimate the model simultaneously. By imposing the adaptive LASSO penalty and starting with the Nadaraya-Watson estimator, the method can identify the constant coefficients and varying coefficients consistently, and estimate the model with oracle efficiency (Fan and Li (2001)).||Source Title:||Statistica Sinica||URI:||http://scholarbank.nus.edu.sg/handle/10635/104986||ISSN:||10170405||DOI:||10.5705/ss.2010.105|
|Appears in Collections:||Staff Publications|
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