Information AboutAutocovariance |
| CATEGORIES ABOUT AUTOCOVARIANCE | |
| covariance and correlation | |
| time series analysis | |
| fourier analysis | |
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: Where E is the Expectation operator. If ''X''''t'' is Second-order Stationary then the following definition becomes the more familiar: : The ''k'' is the amount the signal has been shifted and is usually referred to as the lag. When normalised by dividing by the Variance σ2 then the autocovariance becomes the Autocorrelation ''R''(''k''). That is : Note, however, that some disciplines use the terms autocovariance and autocorrelation interchangeably. The autocovariance can be thought of as a measure of how similar a signal is to a time-shifted version of itself with an autocovariance of σ2 indicating perfect correlation at that lag. The normalisation with the variance will put this into the range {Link without Title} . REFERENCES
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