Content deleted Content added
Mark viking (talk | contribs) Removing the context tag; the intro seems to have enough context to get the basic idea. Of course the article is a stub and needs to be expanded... |
m →External links: HTTP to HTTPS for SourceForge |
||
| (21 intermediate revisions by 20 users not shown) | |||
Line 1:
In [[time series]] modeling, a '''nonlinear autoregressive exogenous model''' (NARX) is a [[nonlinear]] [[autoregressive model]] which has [[exogenous]] inputs. This means that the model relates the current value of a time series
* 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
▲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
Line 16 ⟶ 14:
== 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==
* [
[[Category:Time series models]]
[[Category:Nonlinear time series analysis]]
| |||