When the regressors of a econometric linear model are nonorthogonal, it is well known that their estimation by ordinary least squares can present various problems that discourage the use of this model. The ridge regression is the most commonly used alternative; however, its generalized version has hardly been analyzed. The present work addresses the estimation of this generalized version, as well as the calculation of its mean squared error, goodness of fit and bootstrap inference.

翻译：当计量经济学线性模型的回归变量非正交时，众所周知，采用普通最小二乘法进行估计会产生诸多问题，从而限制了该模型的应用。岭回归是最常用的替代方法；然而，其广义版本的分析尚不充分。本研究探讨了该广义版本的估计方法，并计算了其均方误差、拟合优度及自助法推断。