Volume 14, Issue 4, December 2015, Pages 413 - 424
Correlation Based Ridge Parameters in Ridge Regression with Heteroscedastic Errors and Outliers
Authors
A.V. Dorugade
Corresponding Author
A.V. Dorugade
Received 10 August 2014, Accepted 20 September 2015, Available Online 1 December 2015.
- DOI
- 10.2991/jsta.2015.14.4.6How to use a DOI?
- Keywords
- Heteroscedasticity; Multicollinearity; Mean square error; Outlier; Ridge estimator.
- Abstract
This paper introduces some new estimators for estimating ridge parameter, based on correlation between response and regressor variables for ridge regression analysis. A simulation study has been made to evaluate the performance of proposed estimators based on the minimum mean squared error (MSE) criterion compared to ordinary least squares (LS) estimator and ordinary ridge regression (RR) estimator. The simulation studies demonstrated that the suggested estimators are superior to LS and RR estimators in ridge regression analysis with Heteroscedastic and/or correlated errors, outlier observations.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - A.V. Dorugade PY - 2015 DA - 2015/12/01 TI - Correlation Based Ridge Parameters in Ridge Regression with Heteroscedastic Errors and Outliers JO - Journal of Statistical Theory and Applications SP - 413 EP - 424 VL - 14 IS - 4 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2015.14.4.6 DO - 10.2991/jsta.2015.14.4.6 ID - Dorugade2015 ER -