同求以上问题的答案 纠结中。。。。

调整时间序列的自相关性

调整时间序列的自相关性？
请问，楼上具体调整原理是什么？

The problem in autocorrelation, often found in time series data, is that the error terms are correlated over time. This can be demonstrated in Q * , a matrix of sums of squares and cross products that involves σ(ij) and the rows of X. The least squares estimator b is a consistent estimator of β. This implies that the least squares residuals ei are "point-wise" consistent estimators of their population counterparts Ei. The general approach, then, will be to use X and e to devise an estimator of Q * .[6] What this means is that as the time between error terms increases, the correlation between the error terms decreases. The estimator thus can be used to improve the ordinary least squares (OLS) regression when the variables have heteroskedasticity or autocorrelation.

能请问一下在STATA里面具体怎么做吗？