Description Usage Arguments References Examples

This method implements the fast algorithm proposed by Huo and Székely. The
result of `dcov2d`

and `dcor2d`

is same with the result of
`energy::dcov2d`

and `energy::dcor2d`

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`x` |
the vector of x |

`y` |
the vector of y |

`type` |
"V" or "U", for V- or U-statistics of distance covariance or correlation. The default value is "V". |

Székely, G. J., Rizzo, M. L., & Bakirov, N. K. (2007). Measuring and testing dependence by correlation of distances. The annals of statistics, 35(6), 2769-2794.

Székely, G. J., & Rizzo, M. L. (2013). The distance correlation t-test of independence in high dimension. Journal of Multivariate Analysis, 117, 193-213.

Huo, X., & Székely, G. J. (2016). Fast computing for distance covariance. Technometrics, 58(4), 435-447.

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