It is well known that individual parameters of strongly correlated predictor variables in a linear model cannot be accurately estimated by the least squares regression due to multicollinearity generated by such variables. Surprisingly, an average of these parameters can be extremely accurately estimated. We find this average and briefly discuss its applications in the least squares regression.

翻译：众所周知,线性模型中密切相关的预测变量的个别参数无法精确地用这些变量产生的多曲线性造成的最小平方回归法来估计。奇怪的是,这些参数的平均数可以非常准确地估计。我们发现这一平均数,并简要讨论其在最小平方回归法中的应用。