Principles of Data Science
The Partial Autocorrelation Function (PACF) measures the correlation between a time series and its lagged values after removing the effects of intervening lags. It is a vital tool in identifying patterns and relationships within time series data, helping to determine the appropriate number of lags to include in models like ARIMA.
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