A Normal Approximation for the Distribution of the Likelihood Ratio Statistic in Multivariate Analysis of Variance
针对多元一般线性假设检验中似然比统计量的零分布，提出一种正态近似方法，并与Box和Rao的经典近似比较，发现新方法在变量多或误差自由度小时表现更优。
A normal approximation to the null distribution of the likelihood ratio statistic for testing the multivariate general linear hypothesis is developed. This approximation is compared with the well-known approximations due to Box (1949) and Rao (1948). It is found that the approximations due to Box and Rao deteriorate as the number of variables or, in the terminology of one-way classification, the number of groups increases. Moreover, both approximations give poor results when the number of degrees of freedom for error is small. The normal approximation is nowhere strikingly poor.