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ARIMA stands for AutoRegressive Integrated Moving Average, a popular statistical method used for time series forecasting. It is composed of three main components:
AR (AutoRegressive) Component:
MA (Moving Average) Component:
Grid Search:
Model Evaluation:
The AR and MA components in ARIMA models provide a robust framework for forecasting time series by capturing both the dependencies on past values (AR) and past forecast errors (MA). Understanding and determining the correct orders of these components is crucial for building an effective ARIMA model.