Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
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A procedure for improving the estimate of the mean (in the mean-square sense), compared to &xmarc;, for a weakly-stationary autoregressive time-series is presented. The improvement provided by the procedure is especially evident when only a relatively short sample time-series is available and the power spectrum of the underlying process is not flat (white). A detailed empirical evaluation of the new estimation procedure, based on a simulation analysis, is presented. The new procedure is based on an estimator that would be BLUE (best linear unbiased estimator) if the order and coefficients of the underlying autoregressive process were known. The loss of efficiency caused by estimating the order and coefficients is shown to be small.