Forecasting
Seasonal ARIMA, or Seasonal AutoRegressive Integrated Moving Average, is a statistical modeling technique used for forecasting time series data that exhibits seasonal patterns. It extends the ARIMA model by incorporating seasonal terms, allowing it to capture both non-seasonal and seasonal fluctuations in data, making it particularly effective for datasets with regular seasonal variations.
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