Nonlinear autoregressive exogenous model: Difference between revisions

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* past values of the same series; and

* current and past values of the driving (exogenous) series — that is, of the externally determined series that influences the series of interest.

In addition, the model contains an error term which relates to the fact that knowledge of the other terms will not enable the current value of the time series to be predicted exactly.

In addition, the model contains:

* an "error" term

which relates to the fact that knowledge of the other terms will not enable the current value of the time series to be predicted exactly.

Such a model can be stated algebraically as

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== References ==

* S. A. Billings. "Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains, Wiley, {{ISBN |978-1-1199-4359-4}}, 2013.

* I.J. Leontaritis and S.A. Billings. "Input-output parametric models for non-linear systems. Part I: deterministic non-linear systems". ''Int'l J of Control'' 41:303-328, 1985.

* I.J. Leontaritis and S.A. Billings. "Input-output parametric models for non-linear systems. Part II: stochastic non-linear systems". ''Int'l J of Control'' 41:329-344, 1985.

* O. Nelles. "Nonlinear System Identification". Springer Berlin, {{ISBN |3-540-67369-5}}, 2000.

* W.A. Brock, J.A. Scheinkman, W.D. Dechert and B. LeBaron. "A Test for Independence based on the Correlation Dimension". ''Econometric Reviews'' 15:197-235, 1996.

==External links==

* [httphttps://sourceforge.net/projects/narxsim Open-source implementation of the NARX model using neural networks]

[[Category:Time series models]]