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PACF - Partial Auto Correlation Function (TS E11)
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The PACF (Partial Auto Correlation Function) is one more tool we will need in our time-series tool belt to be able to understand and build better models. The PACF is used to identify AR (Auto Regressive) terms in our data.
The previous video on the ACF was used to identify MA (Moving Average) terms however the terms of an MA are all combined over the lags. The PACF will identify only the correlation and relationship between today and a lagged value while controlling for the lags in between.
ACF video:
Time Series Analysis by Hamilton (affiliate link):
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The previous video on the ACF was used to identify MA (Moving Average) terms however the terms of an MA are all combined over the lags. The PACF will identify only the correlation and relationship between today and a lagged value while controlling for the lags in between.
ACF video:
Time Series Analysis by Hamilton (affiliate link):
Quant t-shirts, mugs, and hoodies:
Connect with me:
☕ Show Your Support and Buy Me a Coffee ☕
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