Particle swarm optimization based Liu-type estimator

Deniz Inan, Erol Egrioglu, Busenur Sarica, Oykum Esra Askin and Mujgan Tez

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 22, 11358-11369

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.

Date: 2017
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DOI: 10.1080/03610926.2016.1267759

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