Particle swarm optimization based Liu-type estimator. Issue 22 (17th November 2017)

• Record Type: Journal Article
• Authors: Inan, Deniz; Egrioglu, Erol; Sarica, Busenur; Askin, Oykum Esra; Tez, Mujgan
• Is Part Of: Communications in statistics. Volume 46:Issue 22(2017)
• Page Start: 11358
• Page End: 11369
• Publication Date: 2017-11-17
• Subjects: Collinearity -- Linear regression -- Liu-type estimator -- Particle swarm optimization -- Ridge regression estimator.; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2016.1267759
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu's method, a ( k, d ) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum ( k, d ) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.