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Published
2023-11-07
Section
Articles
How to Cite
MODELLING AND FORECASTING FOR NONSTATIONARY PROCESS MANAGEMENT
Toir Makhamatkhujaev
Shokhjakhon Abdufattokhov
Keywords: Keywords: Non-stationary processes, linear model, complex systems, random walk.
Abstract
Abstract. Predicting the evolution of complex systems is noted as one of the ten grand challenges of modern science. Time series data from complex systems capture the dynamic behaviours and causalities of the underlying processes and provide a tractable means to predict and monitor system state evolution. However, most of the time series observed in our life are nonstationary, often exhibiting trends which can be seen in several forms. Such trends are often removed by differencing the data an appropriate number of times, in which case the series is known as an integrated process. Box and Jenkins recommended this approach, and it is widely used in many research areas. In the paper, a sequence of main steps of the Box-Jenkins model is highlighted and demonstrated in a case study of the Real Gross Domestic Product of the US example. Several simple cases of the ARMA model are introduced and analyzed, followed by building and selecting an appropriate model to explain the evolution of an observed time series.
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http://www.bea.gov/national/pdf/nipaguid.pdf
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