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Autoregressive (AR) Models

Autoregressive (AR) Models:

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 Math image is a weighted sum of Math image previous values of the filter output. The integer parameter Math image is called the order of the AR-model.

The AR-model of a random process Math image in discrete time Math image is defined by the following expression:


  • Math image are the coefficients of the recursive filter;
  • Math image is the order of the model;
  • Math image are output uncorrelated errors.

See also: moving average models , autoregressive and moving average models (ARMA) , ARIMA .

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