Improving efficiency in fuzzy regression modeling by Stein-type shrinkage
Statistics Theory
2019-03-04 v1 Statistics Theory
Abstract
The fuzzy linear regression (FLR) modeling was first proposed making use of linear programming and then followed by many improvements in a variety of ways. In almost all approaches changing the meters, objective function, and restrictions caused to improve the fuzzy measure of efficiencies (FMEs). In this paper, from a totally different viewpoint, we apply shrinkage estimation strategy to improve FMEs in the FLR modeling. By several illustrative examples, we demonstrate the superiority of the proposed estimation method. In this respect, we show fuzzy shrinkage estimates improve FMEs estimation dramatically compared to the existing methods.
Keywords
Cite
@article{arxiv.1903.00351,
title = {Improving efficiency in fuzzy regression modeling by Stein-type shrinkage},
author = {M. Kashani and M. Arashi and M. R. Rabiei},
journal= {arXiv preprint arXiv:1903.00351},
year = {2019}
}
Comments
14 pages