Two‐parameter estimators have increasing usage in the linear regression model concerning mitigating the problem of multicollinearity. In this type of biased estimators, two different parameters contribute to the solution of two different problems. Previously defined two‐parameter ridge estimator (TPRE) assures considerable merits in this context. This estimator eliminates unfavorable effects of multicollinearity as well as improves the coefficient of multiple determination for the linear regression model. Concerning the TPRE, both the mean square error comparisons and some conventional selection methods for the biasing parameters are available in the literature.

中文翻译：

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两参数岭估计的遗传算法新优化方法的实现与验证

关于减少多重共线性问题的线性回归模型，两参数估计量的使用日益增加。在这种类型的有偏估计量中，两个不同的参数有助于解决两个不同的问题。在此情况下，先前定义的两参数脊线估计器（TPRE）确保了相当大的优势。该估计器消除了多重共线性的不利影响，并提高了线性回归模型的多重确定系数。关于TPRE，均方差比较和偏向参数的一些常规选择方法在文献中均可用。