estats (version 1.0)

Approximate distance variance: Approximate distance variance

Description

Approximate distance variance.

Usage

adcov(x, y, bc = FALSE, K = 100)

Value

The approximate distance covariance.

Arguments

x

A numerical matrix.

y

A numerical matrix.

bc

If you want the bias-corrected distance correlation set this equal to TRUE.

K

The number of projections to perform.

Author

Michail Tsagris and Manos Papadakis.

R implementation and documentation: Michail Tsagris <[e-mail]>.

Details

The approximate distance covariance of Huand and Huo (2022) is computed.

References

Szekely G.J., Rizzo M.L. and Bakirov N.K.(2007). Measuring and Testing Independence by Correlation of Distances. Annals of Statistics, 35(6):2769--2794.

Szekely G. J. and Rizzo M. L. (2023). The Energy of Data and Distance Correlation. Chapman and Hall/CRC.

Huang C. and Huo X. (2022). A statistically and numerically efficient independence test based on random projections and distance covariance. Frontiers in Applied Mathematics and Statistics, 7: 779841.

Tsagris M. and Papadakis M. (2025). Fast and light-weight energy statistics using the R package Rfast. https://arxiv.org/abs/2501.02849

See Also

adcov, adcov.test

Examples

x <- as.matrix(iris[1:50, 1:4])
y <- as.matrix(iris[51:100, 1:4])
res <- dvar(x[, 1])
dcor(x, y)