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Robust SiZer Approach for Varying Coefficient Models
Joint Authors
Zhang, Hui-Guo
Mei, Chang-Lin
Wang, He-Ling
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-09
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Varying coefficient models have widely been applied to many practical fields for exploring dynamic patterns of the regression relationships.
In this study, we propose a robust scenario of SiZer (significant zero crossing of derivatives) inference approach based on the local least absolute deviation fitting procedure and the bootstrap confidence interval to uncover the statistically significant features of the coefficient functions in a varying coefficient model under different smoothing scales.
The simulation study shows that the proposed SiZer approach is quite robust to outliers and performs well in finding the significant features of the coefficient functions.
Furthermore, a real environmental data set is analyzed to demonstrate the application of the proposed approach.
American Psychological Association (APA)
Zhang, Hui-Guo& Mei, Chang-Lin& Wang, He-Ling. 2013. Robust SiZer Approach for Varying Coefficient Models. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1009810
Modern Language Association (MLA)
Zhang, Hui-Guo…[et al.]. Robust SiZer Approach for Varying Coefficient Models. Mathematical Problems in Engineering No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1009810
American Medical Association (AMA)
Zhang, Hui-Guo& Mei, Chang-Lin& Wang, He-Ling. Robust SiZer Approach for Varying Coefficient Models. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1009810
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009810