. IMPROVED PENALTY STRATEGIES in LINEAR REGRESSION MODELS
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inst Nacional Estatistica-Ine
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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.
Açıklama
Anahtar Kelimeler
Sub-model, Full Model, Pretest and Shrinkage Estimation, Multicollinearity, Asymp-totic and Simulation
Kaynak
Revstat-Statistical Journal
WoS Q Değeri
Q4
Scopus Q Değeri
Cilt
15
Sayı
2
