• 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

  • Pages
    8
  • From page
    87
  • To page
    94
  • 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
  • Serial Year
    2018
  • Record number

    2601133