SLASSO: a scaled LASSO for multicollinear situations
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
We propose a re-scaled LASSO by pre-multiplying the LASSO with a matrix term, namely, scaled LASSO (SLASSO), for multicollinear situations. Our numerical study has shown that the SLASSO is comparable with other sparse modeling techniques and often outperforms the LASSO and elastic net. Our findings open new visions about using the LASSO still for sparse modeling and variable selection. We conclude our study by pointing that the same efficient algorithm can solve the SLASSO for solving the LASSO and suggest following the same construction technique for other penalized estimators
Açıklama
Anahtar Kelimeler
Biasing parameter, L-1-penalty, LASSO, Liu estimation, Multicollinearity, variable selection
Kaynak
Journal of Statistical Computation and Simulation
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
91
Sayı
15
