SARIMAXmallit
SARIMAX is a statistical modeling technique used for forecasting and analysis of time series data. It is a class of models that combines the strengths of SARIMA (Seasonal ARIMA) and external regression variables. Developed by Hyndman and Athanasopoulos in 2014, the SARIMAX model is capable of handling complex time series datasets with multiple seasonality components, non-linearity, and exogenous variables.
The basic structure of the SARIMAX model assumes that the time series data can be represented as
SARIMAX models can be estimated using maximum likelihood estimation, and model selection is often performed using
The SARIMAX model has several advantages over traditional SARIMA models, including its ability to handle external