Cross-covariance is a statistical measure that quantifies the degree to which two random variables or stochastic processes vary together. It generalizes the idea of variance, which measures how a single variable varies around its mean, to a pair of variables. Cross-covariance is particularly useful in time series analysis, signal processing, and various fields of statistics and applied mathematics.
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