Variable selection in partially time-varying coefficient models
Date
2009
Authors
Li, Degui
Chen, Jia
Lin, Zhengyan
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Journal of Nonparametric Statistics, 2009; 21(5):553-566
Statement of Responsibility
Degui Li, Jia Chen and Zhengyan Lin
Conference Name
Abstract
A partially time-varying coefficient model is introduced to characterise the nonlinearity and trending phenomenon. To enhance predictability and to select significant variables in the parametric component of the model, the penalised least squares method with the help of the profile local linear technique is developed in this article. The convergence rate and the oracle property of the resulting estimator are established under mild conditions. A remarkable achievement of our results is that it does not require undersmoothing of the nonparametric component. Meanwhile, some extensions of the proposed model and method are also discussed. Furthermore, some numerical examples are provided to show that our theory and method work well in practice.
School/Discipline
School of Economics
Dissertation Note
Provenance
Description
© 2009 Taylor & Francis