An Optimal Selection of Regression Variables
提出了一种渐近最优的回归变量选择方法，假设控制变量数量无限或随样本量增加，并证明Mallows的Cp、Akaike的FPE和AIC方法与此方法渐近等价。
An asymptotically optimal selection of regression variables is proposed. The key assumption is that the number of control variables is infinite or increases with the sample size. It is also shown that Mallows's Cp', Akaike's FPE and aic methods are all asymptotically equivalent to this method.