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Stochastic Process Modeling in a Variable Parameter Framework
Conference presentation

Stochastic Process Modeling in a Variable Parameter Framework

Pragmatic Research: International Symposium on Forecasting, 3rd (Philadelphia, Pennsylvania, USA, 06/05/1983–06/08/1983)
06/1983

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Abstract

A common assumption with time series modeling is that the parameters of the process remain unchanged as the series realization grows. This paper examines the case in which the parameters of a stochastic process the time series model are allowed to vary systematically within a given realization. Specifically, a model is developed that explicitly considers the structure of parametric drift within a given stochastic process. It is shown that models of this type are easily developed and add an element of enhanced precision to the predictive performance of time series forecasts.

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