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Using Exponential Smoothing To Specify Intervention Models for Interrupted Time Series

University of Maryland-Baltimore County

Stuart I. Bretschneider

Syracuse University

In general, procedures for the analysis of interrupted time series are quite sophisticated and powerful. However, procedures for identifying the intervention component of inter rupted time-series models remain relatively primitive. In this article we demonstrate how exponential smoothing can play a function in the identification of the intervention component of an interrupted time-series model that is analogous to the function that the sample autocorrelation and partial autocorrelation functions serve in the identification of the noise portion of such a model.

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