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Bootstrap-based model selection in subset polynomial regression

S., Suparman and Rusiman, Mohd Saifullah (2018) Bootstrap-based model selection in subset polynomial regression. International Journal of Advances in Intelligent Informatics, 4 (2). pp. 87-94. ISSN 24426571

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Abstract

The subset polynomial regression model is wider than the polynomial regression model. This study proposes an estimate of the parameters of the subset polynomial regression model with unknown error and distribution. The Bootstrap method is used to estimate the parameters of the subset polynomial regression model. Simulated data is used to test the performance of the Bootstrap method. The test results show that the bootstrap method can estimate well the parameters of the subset polynomial regression model.

Item Type: Article
Uncontrolled Keywords: Bootstrap algorithm; Subset polynomial; Regression; Model selection;
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 31 Oct 2019 02:33
Last Modified: 31 Oct 2019 02:33
URI: http://eprints.uthm.edu.my/id/eprint/11783
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