The Partial Autocorrelation Function (PACF) measures the correlation between a time series and its own lagged values, controlling for the values of the intervening lags. This function is crucial for identifying the order of an autoregressive model, helping to distinguish the direct relationships between observations at different time points without interference from other lags. It provides insight into the underlying structure of the time series, which is vital for assessing stationarity and understanding autocorrelations.
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