Robust Quadratic Regression and Its Application to Energy-Growth Consumption Problem
Joint Authors
Zhang, Yuli
Wang, Yongzhi
Zhang, Fuliang
Yi, Jining
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-23
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
We propose a robust quadratic regression model to handle the statistics inaccuracy.
Unlike the traditional robust statistic approaches that mainly focus on eliminating the effect of outliers, the proposed model employs the recently developed robust optimization methodology and tries to minimize the worst-case residual errors.
First, we give a solvable equivalent semidefinite programming for the robust least square model with ball uncertainty set.
Then the result is generalized to robust models under l1- and l∞-norm critera with general ellipsoid uncertainty sets.
In addition, we establish a robust regression model for per capital GDP and energy consumption in the energy-growth problem under the conservation hypothesis.
Finally, numerical experiments are carried out to verify the effectiveness of the proposed models and demonstrate the effect of the uncertainty perturbation on the robust models.
American Psychological Association (APA)
Wang, Yongzhi& Zhang, Yuli& Zhang, Fuliang& Yi, Jining. 2013. Robust Quadratic Regression and Its Application to Energy-Growth Consumption Problem. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1031743
Modern Language Association (MLA)
Wang, Yongzhi…[et al.]. Robust Quadratic Regression and Its Application to Energy-Growth Consumption Problem. Mathematical Problems in Engineering No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1031743
American Medical Association (AMA)
Wang, Yongzhi& Zhang, Yuli& Zhang, Fuliang& Yi, Jining. Robust Quadratic Regression and Its Application to Energy-Growth Consumption Problem. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1031743
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031743