Approximate Inferences in Multiresponse Regression Analysis
提出一种多响应回归模型的近似推断方法，用于构建近似置信区间和诊断工具（如标准化残差和影响度量），分两阶段近似：先用估计的误差协方差矩阵替换为广义最小二乘模型，再对非线性模型函数做线性近似。
We present an approximate inference procedure for the multiresponse regression model. This can be used to determine approximate confidence regions or intervals and to formulate diagnostic tools such as standardized residuals and influence measures. The overall approximation is based on approximations at two stages. At the first stage, the multiresponse regression model is replaced by a generalized least-squares model using the estimated variance-covariance matrix of the error terms. At the second stage, the nonlinear model functions are replaced by linear approximations.