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Automatic Variable Selection for Partially Linear Functional Additive Model and Its Application to the Tecator Data Set
Joint Authors
Hu, Yuping
Xue, Liugen
Feng, Sanying
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-16
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We introduce a new partially linear functional additive model, and we consider the problem of variable selection for this model.
Based on the functional principal components method and the centered spline basis function approximation, a new variable selection procedure is proposed by using the smooth-threshold estimating equation (SEE).
The proposed procedure automatically eliminates inactive predictors by setting the corresponding parameters to be zero and simultaneously estimates the nonzero regression coefficients by solving the SEE.
The approach avoids the convex optimization problem, and it is flexible and easy to implement.
We establish the asymptotic properties of the resulting estimators under some regularity conditions.
We apply the proposed procedure to analyze a real data set: the Tecator data set.
American Psychological Association (APA)
Hu, Yuping& Feng, Sanying& Xue, Liugen. 2018. Automatic Variable Selection for Partially Linear Functional Additive Model and Its Application to the Tecator Data Set. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1208014
Modern Language Association (MLA)
Hu, Yuping…[et al.]. Automatic Variable Selection for Partially Linear Functional Additive Model and Its Application to the Tecator Data Set. Mathematical Problems in Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1208014
American Medical Association (AMA)
Hu, Yuping& Feng, Sanying& Xue, Liugen. Automatic Variable Selection for Partially Linear Functional Additive Model and Its Application to the Tecator Data Set. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1208014
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208014