Particle swarm optimization based Liu-type estimator. Issue 22 (17th November 2017) - Inan, Deniz; Egrioglu, Erol; Sarica, Busenur; Askin, Oykum Esra; Tez, Mujgan
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.