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Efficient Model Selection in Semivarying Coefficient Models

Authors
노호석Ingrid Van Keilegom
Issue Date
2012
Publisher
INST MATHEMATICAL STATISTICS
Citation
ELECTRONIC JOURNAL OF STATISTICS, pp.2519 - 2534
Journal Title
ELECTRONIC JOURNAL OF STATISTICS
Start Page
2519
End Page
2534
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/147670
Abstract
Varying coefficient models are useful extensions of classical linear models. In practice, some of the coefficients may be just constant, while other coefficients are varying. Several methods have been developed to utilize the information that some coefficient functions are constant to improve estimation efficiency. However, in order for such methods to really work, the information about which coefficient functions are constant should be given in advance. In this paper, we propose a computationally efficient method to discriminate in a consistent way the constant coefficient functions from the varying ones. Additionally, we compare the performance of our proposal with that of previous methods developed for the same purpose in terms of model selection accuracy and computing time.
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