An ARMA (AutoRegressive Moving Average) model is a statistical tool used for time series forecasting. It combines two components: autoregression (AR), which uses past values of the series, and moving average (MA), which uses past forecast errors. ARMA models are ideal for stationary time series data, and their parameters (p, q) help define the model’s structure. They are widely used in fields like economics and finance for predicting future values.
