Article ID: | iaor19941228 |
Country: | United States |
Volume: | 39 |
Issue: | 8 |
Start Page Number: | 1002 |
End Page Number: | 1019 |
Publication Date: | Aug 1993 |
Journal: | Management Science |
Authors: | Bischak Diane, Kelton David, Pollock Stephen |
Keywords: | statistics: inference, time series & forecasting methods |
The authors propose a new procedure for providing confidence-interval estimators of the mean of a covariance-stationary process. The procedure, a modification of the method of batch means, is an improvement over existing methods when the process displays strong correlation and a comparatively small number of observations is available. They assign weights to the observations within a batch. The weights are determined by the order of the time-series model fit to the process and by its estimated parameters. For a given model and its parameters, the weights minimize the variance of the weighted point estimator of the mean; the point and variance estimators formed when these optimal weights are applied are unbiased. The time-series identification procedure and estimation of the parameters and weights bring in bias. Formulas for optimal weights are given for AR(