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基于未分类初始样本的线性判别函数效率AI 解读

Estimation of the optimal linear discriminant function is considered on the basis of a sample of observations known only to belong to a mixture of two univariate normal populations with a common variance. The asymptotic efficiency of the procedure so obtained is evaluated relative to that of Anderson's classification statistic.

基于未分类初始样本的线性判别函数效率AI 解读

Estimation of the optimal linear discriminant function is considered on the basis of a sample of observations known only to belong to a mixture of two univariate normal populations with a common variance. The asymptotic efficiency of the procedure so obtained is evaluated relative to that of Anderson's classification statistic.