20th Nov 2023

Seasonal Autoregressive Integrated Moving Average (SARIMA) is an advanced time series forecasting model that extends the ARIMA framework to incorporate seasonality. It includes seasonal autoregressive (SAR), seasonal differencing (Seasonal I), and seasonal moving average (SMA) components, enabling the modeling and prediction of time series data with recurring patterns over specific time intervals. SARIMA is particularly valuable in applications where seasonality significantly influences data trends, such as retail sales, climate patterns, or economic indicators. By considering both non-seasonal and seasonal dynamics, SARIMA enhances the accuracy of forecasts, providing a versatile tool for analysts and researchers in various domains.