Suparman, S. 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 2442-6571

Text
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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 |
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Uncontrolled Keywords: | Bootstrap algorithm; Subset polynomial; Regression; Model selection |

Subjects: | Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics T Technology > TA Engineering (General). Civil engineering (General) > TA329-348 Engineering mathematics. Engineering analysis |

Divisions: | Faculty of Applied Science and Technology > Department of Mathematics and Statistics |

Depositing User: | UiTM Student Praktikal |

Date Deposited: | 05 Jan 2022 08:37 |

Last Modified: | 05 Jan 2022 08:37 |

URI: | http://eprints.uthm.edu.my/id/eprint/5108 |

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