Generalized ridge estimator shrinkage estimation based on particle swarm optimization algorithm


It is well-known that in the presence of multicollinearity, the ridge estimator is an alternative to the ordinary least square (OLS) estimator. Generalized ridge estimator (GRE) is an generalization of the ridge estimator. However, the efficiency of GRE depends on appropriately choosing the shrinkage parameter matrix which is involved in the GRE. In this paper, a particle swarm optimization method, which is a metaheuristic continuous algorithm, is proposed to estimate the shrinkage parameter matrix. The simulation study and real application results show the superior performance of the proposed method in terms of prediction error.

DOI Code: 10.1285/i20705948v14n1p254

Keywords: Multicollinearity; shrinkage parameter; generalized ridge estimator; particle swarm optimization.

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