Asymptotic Efficiency of Logistic Regression Relative to Linear Discriminant Analysis
计算了当解释变量服从正态分布时，逻辑回归相对于线性判别分析在参数假设检验中的渐近效率，发现该效率与变量数和待检参数数无关。
We calculate the asymptotic efficiency of logistic regression relative to linear discriminant analysis for testing hypotheses about the parameters when the explanatory variables are normally distributed. The Pitman asymptotic efficiency for hypothesis tests in this context is the same as the asymptotic relative efficiency calculated using mis-classification rates and is independent of the number of explanatory variables and the number of parameters to be tested.