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The Partial Auto Correlation Coefficient (PACC) is an estimate of the additional correlation between the data value at time 't' and the data value at time (t-k), after adjusting for the correlation of the values between time 't' and the data value at time (t-k). Partial Auto Correlation Coefficients are used when constructing ARIMA models for time series data. For each Partial Auto Correlation, a corresponding Standard Error is calculated. If the time series is random, all of the Partial Auto Correlations should be within approximately +/- 2 Standard Errors. When constructing an Auto regressive model (AR), a partial auto correlation estimate extending beyond this distance indicates the need for a coefficient at the indicated time lag.
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