ARMA models, or Autoregressive Moving Average models, are a class of statistical models used for analyzing and forecasting time series data. They combine two key components: autoregression, which uses past values of the series to predict future values, and moving averages, which incorporate past forecast errors into the prediction. This blend allows ARMA models to capture various patterns in time series data, making them essential tools in econometrics and signal processing.
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