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Feasible Stein-Type and Preliminary Test Estimations in the System Regression Model
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Resumo(s)
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.
Descrição
Publisher Copyright:
© 2023 International Academic Press
Palavras-chave
Feasible generalized least squares estimator LASSO Preliminary test estimation Seemingly unrelated regression models Shrinkage estimation Stein-type estimation Signal Processing Statistics and Probability Information Systems Computer Vision and Pattern Recognition Statistics, Probability and Uncertainty Control and Optimization Artificial Intelligence