2022
DOI: 10.1016/j.chaos.2022.111868
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The dependence measurements based on martingale difference correlation and distance correlation: Efficient tools to distinguish different complex systems

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Cited by 4 publications
(1 citation statement)
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“…However, this does not necessarily mean that the two variables are independent of each other because there may well be other relationships between them. The distance correlation coefficient can measure the linear and nonlinear relationship between two variables, and when the distance correlation coefficient takes the value of 0, the two variables are independent of each other, because the characteristic function can uniquely determine the probability distribution of the random variable, and the probability density function of the random variable and the characteristic function can be related by the Fourier transform when the characteristic function is under the condition of absolute productibility [18].…”
Section: Distance Correlation Coefficientmentioning
confidence: 99%
“…However, this does not necessarily mean that the two variables are independent of each other because there may well be other relationships between them. The distance correlation coefficient can measure the linear and nonlinear relationship between two variables, and when the distance correlation coefficient takes the value of 0, the two variables are independent of each other, because the characteristic function can uniquely determine the probability distribution of the random variable, and the probability density function of the random variable and the characteristic function can be related by the Fourier transform when the characteristic function is under the condition of absolute productibility [18].…”
Section: Distance Correlation Coefficientmentioning
confidence: 99%