Efficiency of Ordinary Least Squares for Linear Models with Autocorrelation
自相关线性模型中普通最小二乘法的效率
This article provides a reconsideration of Kramer's (1980) results on least squares estimation in linear models with autocorrelated errors. Kramer's results are shown to be dependent on his measure of efficiency and to understate the advantages of correcting for autocorrelation.