SARIMA stands for Seasonal Autoregressive Integrated Moving Average, which is an extension of the ARIMA model that incorporates seasonal effects. This model is particularly useful when dealing with time series data that displays patterns or trends over specific intervals, allowing for more accurate forecasting by accounting for seasonality. SARIMA combines differencing, autoregression, and moving averages to handle both non-seasonal and seasonal components, making it a powerful tool in advanced forecasting techniques.
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