SARIMA, or Seasonal Autoregressive Integrated Moving Average, is a statistical model used for analyzing and forecasting time series data that exhibits both trend and seasonal patterns. This model extends the ARIMA framework by adding seasonal components to capture periodic fluctuations in the data, making it especially useful for datasets that show consistent patterns at regular intervals. By incorporating both autoregressive and moving average elements along with differencing, SARIMA provides a comprehensive approach to understanding complex time series behaviors.
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