We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
RANK THEORY APPROACH TO RIDGE, LASSO, PRELIMINARY TEST AND STEIN-TYPE ESTIMATORS: COMPARATIVE STUDY.
- Authors
SALEH, A. K. MD. EHSANES; NAVRÁATIL, RADIM
- Abstract
In the development of efficient predictive models, the key is to identify suitable predictors for a given linear model. For the first time, this paper provides a comparative study of ridge regression, LASSO, preliminary test and Stein-type estimators based on the theory of rank statistics. Under the orthonormal design matrix of a given linear model, we find that the rank based ridge estimator outperforms the usual rank estimator, restricted R-estimator, rank-based LASSO, preliminary test and Stein-type R-estimators uniformly. On the other hand, neither LASSO nor the usual R-estimator, preliminary test and Stein-type R-estimators outperform the other. The region of domination of LASSO over all the R-estimators (except the ridge R-estimator) is the interval around the origin of the parameter space. Finally, we observe that the L2-risk of the restricted R-estimator equals the lower bound on the L2-risk of LASSO. Our conclusions are based on L2-risk analysis and relative L2-risk efficiencies with related tables and graphs.
- Subjects
ESTIMATION theory; RIDGE regression (Statistics); COMPARATIVE studies; GAUSSIAN distribution; ORTHONORMAL basis
- Publication
Kybernetika, 2018, Vol 54, Issue 5, p958
- ISSN
0023-5954
- Publication type
Article
- DOI
10.14736/kyb-2018-5-0958