The partial autocorrelation function (PACF) measures the correlation between a time series and its own lagged values, controlling for the effects of intermediate lags. This function helps identify the extent of the relationship between observations at different time points while removing the influence of other lags, making it a crucial tool for understanding time series data and constructing ARIMA models.
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