Temporal aggregation is an intuitively appealing approach to deal with demand uncertainty. There are two types of temporal aggregation: non-overlapping and overlapping. Most the supply chain forecasting literature has focused so far on former there no research that analyses latter for auto-correlated demands. In addition, most analytical to-date assumes infinite series’ lengths whereas, in prac...

The following notes illustrate the problem of temporally autocorrelated regression residuals that may arise when using time-series data (and represent the most common violation of the independent-residual assumption in regression modeling). Here the Durbin-Watson statistic is shown to provide diagnostic tool for identifying temporal autocorrelation, and the method of two-stage least squares is ...

This paper reviews some properties of the set of vectors with autocorrelated components. This set appears in some signal processing problems, in particular lter synthesis or statistical estimation. It turns out to be a closed convex cone enjoying several representations and various geometrical properties. The aim of this paper is to gather di erent aspects of the geometry of this cone. We adopt...

Serial correlation can seriously affect the performance of traditional control charts. Many authors have studied the effect of autocorrelation on EWMA control charts and have shown how to modify the control limits to account for autocorrelation. In this paper we compare three different estimation methods for the variance of the EWMA statistic that is adapted to autocorrelated data. This compari...