The GLS Transformation Matrix and a Semi-recursive Estimator for the Linear Regression Model with ARMA Errors
推导了ARMA(p,q)误差协方差矩阵的逆的分解矩阵R的精确形式，用于将带ARMA误差的线性回归模型转化为白噪声误差模型，并应用于半递归估计。
For a general stationary ARMA( p,q ) process u we derive the exact form of the orthogonalizing matrix R such that R ′ R = Σ −1 , where Σ = E ( uu ′) is the covariance matrix of u , generalizing the known formulae for AR ( p ) processes. In a linear regression model with an ARMA( p,q ) error process, transforming the data by R yields a regression model with white-noise errors. We also consider an application to semi-recursive (being recursive for the model parameters, but not for the parameters of the error process) estimation.