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- Title
Comparative Study of LASSO, Ridge Regression, Preliminary Test and Stein-type Estimators for the Sparse Gaussian Regression Model.
- Authors
Saleh, A. K. Md. Ehsanes; Kibria, B. M. Golam; George, Florence
- Abstract
This paper compares the performance characteristics of penalty estimators, namely, LASSO and ridge regression (RR), with the least squares estimator (LSE), restricted estimator (RE), preliminary test estimator (PTE) and the Stein-type estimators. Under the assumption of orthonormal design matrix of a given regression model, we find that the RR estimator dominates the LSE, RE, PTE, Stein-type estimators and LASSO estimator uniformly, while, similar to [17], neither LASSO nor LSE, PTE and Stein-Type estimators dominates the other. Our conclusions are based on the analysis of L2-risks and relative risk efficiencies (RRE) together with the RRE related tables and graphs.
- Subjects
REGRESSION analysis; MULTICOLLINEARITY; LEAST squares; COMPARATIVE studies; MIMO radar; PROSTHODONTICS
- Publication
Statistics, Optimization & Information Computing, 2019, Vol 7, Issue 4, p626
- ISSN
2311-004X
- Publication type
Article
- DOI
10.19139/soic-2310-5070-713