New approaches for determining the degree of differencing necessary to induce stationarity in ARIMA models

In this article we present two methods for determining the degree of differencing required to induce stationarity in the data. These procedures are iterative and consist in systematically fitting increasing order ARIMA and ARI structures to the data, and then verifying that the resulting residuals b...

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Bibliographic Details
Published in:Journal of statistical planning and inference 1993-08, Vol.36 (2), p.399-412
Main Authors: Koreisha, Sergio G., Pukkila, Tarmo M.
Format: Article
Language:English
Subjects:
ARIMA
Autoregressive order determination criterion
differencing
Exact sciences and technology
identification
Inference from stochastic processes
time series analysis
Mathematics
Probability and statistics
Sciences and techniques of general use
stationarity
Statistics
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Summary:In this article we present two methods for determining the degree of differencing required to induce stationarity in the data. These procedures are iterative and consist in systematically fitting increasing order ARIMA and ARI structures to the data, and then verifying that the resulting residuals behave like white noise using an autoregressive order determination criterion. Simulation results of different model structures with varying number of observations are used to evaluate the approaches.
ISSN:0378-3758
1873-1171
DOI:10.1016/0378-3758(93)90140-2