Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Statistical software in APL: Bibliography
APL '79 Proceedings of the international conference on APL: part 1
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A great deal of data in business, economics, engineering and the natural sciences occur in the form of time series where observations are dependent and where the nature of this dependence is of interest in itself. The technics used in the analysis of such series of dependent observations is called time series analysis. The purpose is to build stochastic models for discrete time series and to use these models. In this paper is described the ARIMA-process, the time series analyzing method introduced by Box and Jenkins. In addition is described a set of APL-functions for interactive time series analysis. These functions are based on the concents of multiplication and division of time series, which are introduced in this paper.