TY - JOUR
T1 - Feasible Stein-Type and Preliminary Test Estimations in the System Regression Model
AU - Norouzirad, Mina
AU - Arashi, Mohammad
AU - Marques, Filipe J.
AU - Khan, Naushad A. Mamode
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00297%2F2020/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00297%2F2020/PT#
Publisher Copyright:
© 2023 International Academic Press
PY - 2023
Y1 - 2023
N2 - In a system of regression models, finding a feasible shrinkage is demanding since the covariance structure is unknown and cannot be ignored. On the other hand, specifying sub-space restrictions for adequate shrinkage is vital. This study proposes feasible shrinkage estimation strategies where the sub-space restriction is obtained from LASSO. Therefore, some feasible LASSO-based Stein-type estimators are introduced, and their asymptotic performance is studied.
AB - In a system of regression models, finding a feasible shrinkage is demanding since the covariance structure is unknown and cannot be ignored. On the other hand, specifying sub-space restrictions for adequate shrinkage is vital. This study proposes feasible shrinkage estimation strategies where the sub-space restriction is obtained from LASSO. Therefore, some feasible LASSO-based Stein-type estimators are introduced, and their asymptotic performance is studied.
KW - Feasible generalized least squares estimator
KW - LASSO
KW - Preliminary test estimation
KW - Seemingly unrelated regression models
KW - Shrinkage estimation
KW - Stein-type estimation
UR - http://www.scopus.com/inward/record.url?scp=85152453272&partnerID=8YFLogxK
U2 - 10.19139/soic-2310-5070-1589
DO - 10.19139/soic-2310-5070-1589
M3 - Article
AN - SCOPUS:85152453272
SN - 2311-004X
VL - 11
SP - 258
EP - 275
JO - Statistics, Optimization and Information Computing
JF - Statistics, Optimization and Information Computing
IS - 2
ER -