On modified maximum likelihood estimators of the autocorrelation coeffcient in linear models
线性模型自相关系数的修正最大似然估计量
Two approximations to the maximum likelihood estimiator of the autocorrelation coefficient in first-order Markov disturbances in a linear model have been previously suggested by Durbin & Watson. A Monte Carlo study shows that one of these estimators is less absolutely biased and has smaller variance than the exact maximum likelihood estimator. Further, this estimator exhibits greater power in tests of autocorrelation when used in place of the standard Durbin-Watson…