| 1. | It contrasts with the autocorrelation function, which does not control for other lags.
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| 2. | The autocorrelation function is a statistic defined as
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| 3. | This autocorrelation function has a peak at the origin, where the original source was.
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| 4. | Thus { x _ n } cannot be distinguished from white noise using the autocorrelation function.
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| 5. | Given the time series x [ t ], its non-stationary autocorrelation function is given by
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| 6. | Let the aperiodic autocorrelation function of the sequence "'x "'be defined by
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| 7. | These algorithms derive from the exact theoretical relation between the partial autocorrelation function and the autocorrelation function.
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| 8. | These algorithms derive from the exact theoretical relation between the partial autocorrelation function and the autocorrelation function.
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| 9. | Here, \ ddot ( 0 ) is the second derivative of the autocorrelation function evaluated at zero.
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| 10. | The Siegert equation relates the second-order autocorrelation function with the first-order autocorrelation function as follows:
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