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Results of search for AR follow:

AR: Stands for "autoregressive." Describes a stochastic process (denote here, et) that can be described by a weighted sum of its previous values and a white noise error. An AR(1) process is a first-order one, meaning that only the immediately previous value has a direct effect on the current value:
et = ret-1 + ut
where r is a constant that has absolute value less than one, and ut is drawn from a distribution with mean zero and finite variance, often a normal distribution.
An AR(2) would have the form:
et = r1et-1 + r2et-2 + ut
and so on. In theory a process might be represented by an AR(infinity).

Contexts: time series; econometrics; statistics


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