PACF, or Partial Autocorrelation Function, measures the correlation between a time series and its own past values while controlling for the values of intervening observations. This helps identify the direct relationship between an observation and its lags without interference from other lags, making it crucial for determining the appropriate order of autoregressive terms in ARIMA models.
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