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Seasonal Autoregressive Moving-Average Model


A seasonal autoregressive moving-average model, denoted SARMA(p,q)×(P,Q)_s, is an autoregressive moving-average model with additional autoregressive and moving-average terms at integer multiples of a seasonal period s. Using the shift operator B defined by BX_t=X_(t-1), a centered model can be written

 phi(B)Phi(B^s)X_t=theta(B)Theta(B^s)epsilon_t,

where phi and theta are respectively the nonseasonal autoregressive and moving-average polynomials, Phi and Theta are their seasonal counterparts, and the epsilon_t are innovations. The orders p and q give the degrees of phi and theta, while P and Q give the degrees of Phi and Theta. When P=Q=0, the model reduces to an autoregressive moving-average model.

A seasonal autoregressive moving-average process can be represented in the Wolfram Language using SARMAProcess[a, b, {s, alpha, beta}, v].


See also

Autoregressive Moving-Average Model, Innovation, Stationary Time Series, Time Series Analysis

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References

Box, G. E. P.; Jenkins, G. M.; Reinsel, G. C.; and Ljung, G. M. Time Series Analysis: Forecasting and Control, 5th ed. Hoboken, NJ: Wiley, 2015.

Cite this as:

Weisstein, Eric W. "Seasonal Autoregressive Moving-Average Model." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/SeasonalAutoregressiveMoving-AverageModel.html

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