An autoregressive (AR) model is a type of statistical model used for analyzing and forecasting time series data. It is based on the idea that the current value of a time series can be expressed as a linear combination of its previous values. The basic concept is that past values have a direct influence on current values, allowing the model to capture temporal dependencies.
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