On the Efficiency of the Sample Mean in Long‐memory Noise

When estimating the unknown mean of a stationary time series, the best linear unbiased estimator is often a significantly better estimator than the ordinary least squares estimates X̄ n . The relative efficiency of these two estimators is investigated for time series whose spectrum behaves like a power at the origin (e.g., fractional Gaussian noise and fractional ARIMA).