Bootstrap-based model selection in subset polynomial regression

International Journal of Advances in Intelligent Informatics

View Publication Info
 
 
Field Value
 
Title Bootstrap-based model selection in subset polynomial regression
 
Creator Suparman, Suparman
Rusiman, Mohd Saifullah
 
Subject Bootstrap algorithm; Subset polynomial; Regression; Model selection
 
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.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2018-07-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/173
10.26555/ijain.v4i2.173
 
Source International Journal of Advances in Intelligent Informatics; Vol 4, No 2 (2018): July 2018; 87-94
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/173/ijain_v4i2_p87-94
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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