Discriminant Functions When Covariance Matrices are Unequal
协方差矩阵不等时的判别函数
This study compares by Monte Carlo methods the performance of three discriminant functions in classifying individuals into two multivariate normally distributed populations when covariance matrices are unequal—the quadratic, best linear and Fisher's linear discriminant function. The comparison is carried out both asymptotically and using samples. The expected value of the probabilities is used as the measure of performance. Parameters that are varied in the study include the…