The autoregressive (AR) models are used in time series analysis
. to describe stationary time series
. These models represent time series
that are generated by passing the white noise
through a recursive
linear filter
. The output of such a filter at the moment
is a weighted sum of
previous values of the filter output. The integer parameter
is called the order of the AR-model.
The AR-model of a random process
in discrete time
is defined by the following expression:
where
-
are the coefficients of the recursive filter;
-
is the order of the model;
-
are output uncorrelated errors.
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