Title :
A new algorithm for variable selection
Author :
Bortolin, Gianantonio ; Gutman, Per-Olof
Author_Institution :
Dept. of Math., R. Inst. of Technol., Stockholm
Abstract :
A new method for variable selection and estimation called iteratively scaled ridge regression, ISRR, is proposed. The method is an iterative algorithm based on ridge regression. Simulation studies show that ISRR shares the properties of both subset selection and ridge regression. It selects an optimal subset of the regressor variables and is robust to small changes in the data set. The ISRR algorithm was primarily developed for linear models, but is quite simple and general and can easily be extended to more general linear and nonlinear models
Keywords :
iterative methods; regression analysis; iterative algorithm; iteratively scaled ridge regression; variable estimation; variable selection; Computational modeling; Constraint optimization; Equations; Input variables; Iterative algorithms; Least squares methods; Predictive models; Robustness; USA Councils; Uncertainty;
Conference_Titel :
Decision and Control, 2006 45th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-0171-2
DOI :
10.1109/CDC.2006.376828
