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Time Series Forecasting Based on the Logistic Curve

Journal of the Operational Research SocietyPublished 1 July 1984
Andrew Harvey
Citations48
SJR quartileQ1
SJR score0.92
SNIP1.26

Abstract

AbstractThis paper presents a class of models which are designed for forecasting the net sales of a product when the stock of that product is believed to be subject to a saturation level. The forecast function for the stock takes the form of a general modified exponential, a family which includes the logistic as a special case. However, framing the model in terms of the net increase in the product enables a link to be made between the traditional approach to forecasting based on non-linear trend curves and the approach based on ARIMA models.Keywords: forecastingtrend curvesARIMA modelslogistic curvegeneral modified exponentialstime series

Keywords

Decision SciencesMathematics