The partial autocorrelation function (PACF) measures the correlation between a time series and its lagged values, after removing the effects of intermediate lags. It helps to identify the direct relationship between an observation and its past values, providing insights into the underlying structure of a time series. The PACF is crucial for model identification in time series analysis, especially when determining the order of autoregressive models.
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