An Updated Literature Review of Distance Correlation and its Applications to Time Series
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Abstract (arXiv)
The concept of distance covariance/correlation was introduced recently to characterize dependence among vectors of random variables. We review some statistical aspects of distance covariance/correlation function and we demonstrate its applicability to time series analysis. We will see that the auto-distance covariance/correlation function is able to identify nonlinear relationships and can be employed for testing the i.i.d. hypothesis. Comparisons with other measures of dependence are included.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Oct 2017.
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2 papers.