The partial autocorrelation function (PACF) is a tool used in time series analysis that measures the correlation between a time series and a lagged version of itself, while controlling for the effects of intervening lags. It helps in identifying the direct relationship between a given observation and its past values without the influence of other observations in between. PACF is crucial in determining the appropriate order of an autoregressive model, which is essential for accurate forecasting.
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