Bootstrap-based model selection in subset polynomial regression

Suparman Suparman (Universitas Ahmad Dahlan)
Mohd Saifullah Rusiman (Universiti Tun Hussein Onn Malaysia)

International Journal of Advances in Intelligent Informatics
Vol 4, No 2 (2018): July 2018

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.