Discriminant Analysis Using Least Absolute Deviations
提出一种更简单且具有不变性的最小绝对偏差回归判别方法，模拟显示其在正态和重尾分布下效果不逊于已有方法。
ABSTRACT Several linear programming methods have been suggested as discrimination procedures. A least absolute deviations regression procedure is developed here which is simpler to use and does not suffer from any lack of invariance. A simulation study shows it to be at least as effective as any of the methods previously discussed for normal and heavy‐tailed distributions.