Bootstrap-based model selection in subset polynomial regression

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 regr...

Full description

Bibliographic Details
Main Authors: Suparman, S., Rusiman, Mohd Saifullah
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/5108/1/AJ%202018%20%28835%29%20Bootstrap-based%20model%20selection%20in%20subset%20polynomial%20regression.pdf
_version_ 1825709965795393536
author Suparman, S.
Rusiman, Mohd Saifullah
author_facet Suparman, S.
Rusiman, Mohd Saifullah
author_sort Suparman, S.
collection UTHM
description 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.
first_indexed 2024-03-05T21:50:25Z
format Article
id uthm.eprints-5108
institution Universiti Tun Hussein Onn Malaysia
language English
last_indexed 2024-03-05T21:50:25Z
publishDate 2018
publisher Universitas Ahmad Dahlan
record_format dspace
spelling uthm.eprints-51082022-01-05T08:37:17Z http://eprints.uthm.edu.my/5108/ Bootstrap-based model selection in subset polynomial regression Suparman, S. Rusiman, Mohd Saifullah QA273-280 Probabilities. Mathematical statistics TA329-348 Engineering mathematics. Engineering analysis 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. Universitas Ahmad Dahlan 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5108/1/AJ%202018%20%28835%29%20Bootstrap-based%20model%20selection%20in%20subset%20polynomial%20regression.pdf 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
spellingShingle QA273-280 Probabilities. Mathematical statistics
TA329-348 Engineering mathematics. Engineering analysis
Suparman, S.
Rusiman, Mohd Saifullah
Bootstrap-based model selection in subset polynomial regression
title Bootstrap-based model selection in subset polynomial regression
title_full Bootstrap-based model selection in subset polynomial regression
title_fullStr Bootstrap-based model selection in subset polynomial regression
title_full_unstemmed Bootstrap-based model selection in subset polynomial regression
title_short Bootstrap-based model selection in subset polynomial regression
title_sort bootstrap based model selection in subset polynomial regression
topic QA273-280 Probabilities. Mathematical statistics
TA329-348 Engineering mathematics. Engineering analysis
url http://eprints.uthm.edu.my/5108/1/AJ%202018%20%28835%29%20Bootstrap-based%20model%20selection%20in%20subset%20polynomial%20regression.pdf
work_keys_str_mv AT suparmans bootstrapbasedmodelselectioninsubsetpolynomialregression
AT rusimanmohdsaifullah bootstrapbasedmodelselectioninsubsetpolynomialregression