Moving average (MA) models are used in time series analysis to describe stationary time series . The MA-models represent time series that are generated by passing the white noise through a non-recursive linear filter .

A moving average model of a random process in discrete time is defined by the following expression:

• are the coefficients of the linear non-recursive filter;

• is the order of the MA-model;

• are elements of the (input) white noise;

• are the output uncorrelated errors.

See also the short course Time Series Forecasting .

See also: autoregressive models , autoregressive and moving average models , ARIMA , and the short course Time Series Forecasting .