Inference About Multivariate Means for a Nonstationary Autoregressive Model
研究了协方差矩阵服从前依赖模型（一种一般一阶自回归模型）时多元均值的推断问题，提出了两个替代Hotelling T²检验的统计量，并扩展到多元线性模型。
Abstract Inference about multivariate means is investigated for the case in which the covariance matrix is assumed to follow an antedependence model, which is a general first-order autoregressive model. We present two test statistics that offer alternatives to Hotelling's T 2 test for testing whether a vector mean is equal to some specified value. These antedependence statistics have simple representations in terms of Hotelling's T 2 statistics computed for certain bivariate and univariate variables. Extensions to the multivariate linear model provide easy-to-compute antedependence analogs to the usual Wilk's lambda, Lawley-Hotelling trace, and Pillai's trace statistics.