. IMPROVED PENALTY STRATEGIES in LINEAR REGRESSION MODELS


YÜZBAŞI B. , Ahmed S. E. , GÜNGÖR M.

REVSTAT-STATISTICAL JOURNAL, cilt.15, ss.251-276, 2017 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 15 Konu: 2
  • Basım Tarihi: 2017
  • Dergi Adı: REVSTAT-STATISTICAL JOURNAL
  • Sayfa Sayıları: ss.251-276

Özet

We suggest pretest and shrinkage ridge estimation strategies for linear regression models. We investigate the asymptotic properties of suggested estimators. Further, a Monte Carlo simulation study is conducted to assess the relative performance of the listed estimators. Also, we numerically compare their performance with Lasso, adaptive Lasso and SCAD strategies. Finally, a real data example is presented to illustrate the usefulness of the suggested methods.