Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6420790 | Applied Mathematics and Computation | 2014 | 11 Pages |
â¢A stochastic restricted two-parameter estimator is proposed.â¢The superiority of the new biased estimator over some other estimators is discussed.â¢The selections of the biasing parameters are discussed.
SakallıoÄlu and Kaçiranlar (2008) proposed an estimator, two-parameter estimator, as an alternative to the ordinary least squares, the ordinary ridge and the Liu estimators in the presence of multicollinearity. In this paper, we introduce a new class estimator by combining the ideas underlying the mixed estimator and the two-parameter estimator when stochastic linear restrictions are assumed to hold. The necessary and sufficient conditions for the superiority of the new estimator over the two-parameter estimator, modified mixed estimator and stochastic restricted two-parameter estimator Yang and Wu (2012) are derived by the matrix mean square error criterion. Furthermore, selections of the biasing parameters are discussed and two numerical examples and a Monte Carlo simulation are given to evaluate the performance of mentioned estimators in the theoretical results.