An autoregressive term is a component of a statistical model that uses previous values of a variable to predict its current value. This concept is fundamental in time series analysis, where the model assumes that past observations contain valuable information for forecasting future values, making it essential for building ARIMA models, which integrate autoregressive processes.
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