Title of article :
Bootstrap-based model selection in subset polynomial regression
Author/Authors :
Suparman, Universitas Ahmad Dahlan - Yogyakarta, Indonesia , Rusiman, Mohd Saifullah Universiti Tun Hussein Onn Malaysia - Pagoh, Malaysia
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.
Keywords :
Model selection , Regression , Subset polynomial , Bootstrap algorithm
Journal title :
International Journal of Advances in Intelligent Informatics