Particle swarm optimization based Liu-type estimator |
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Authors: | Deniz Inan Erol Egrioglu Busenur Sarica Oykum Esra Askin Mujgan Tez |
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Affiliation: | 1. Department of Statistics, Marmara University, Istanbul, Turkey;2. Department of Statistics, Giresun University, Giresun, Turkey;3. Department of Statistics, Yildiz Technical University, Istanbul, Turkey |
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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. |
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Keywords: | Collinearity Linear regression Liu-type estimator Particle swarm optimization Ridge regression estimator. |
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