Last updated August 16, 2023
What is ARIMA?
ARIMA (AutoRegressive Integrated Moving Average) is an extension of the another , , that incorporates differencing (integration) to handle non-stationary data. Non-stationary data refers to data that exhibits trends, , or other time-dependent patterns.
What are the components of ARIMA?
- Differencing: If the data is non-stationary, differencing is applied to make it stationary. Differencing involves calculating the differences between consecutive observations to remove trends or seasonality.
- Autoregressive (AR) and (MA) components: After differencing, the AR and MA components are applied to the differenced data to capture any remaining autocorrelation and moving average patterns.