Autoregressive Moving-Average Generator

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The autoregressive moving-average process (ARMA) is a discrete-time and continuous-state random process. This generator randomly chooses parameters of the model from the interval ; you can set the condition for (weak) stationarity.

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Part of the output includes the autocorrelation function (ACF), partial autocorrelation function (PACF), and their samples (SACF, SPACF), which serve as a basic tool for model identification in the Box–Jenkins approach by looking for so-called cut-off points.

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Contributed by: Matus Baniar (June 2013)
Open content licensed under CC BY-NC-SA


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References

[1] T. Cipra, Finanční ekonometrie, Praha, Czech Republic: Ekopress, 2008.

[2] Z. Prášková, Základy náhodných procesů II, Praha, Czech Republic: Karolinum, 2004.



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