Nonlinear autoregressive exogenous model: Difference between revisions

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Revision as of 22:17, 19 July 2008

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Here ''y'' is the variable of interest, and ''u'' is some other variable which is associated with ''y''. In this scheme, information about ''u'' helps predict ''y''. Here <math>\varepsilon</math> is the error or residual term (sometimes called noise). For example, ''y'' may be air temperature at noon, and ''u'' may be the day of the year (day-number within year).

The function ''F'' is some nonlinear function, such as a [[polynomial]]. In some applications, ''F'' is a [[neural network]]. To test for non linearity in a time Series, see [[BDS]]

== References ==