dcor_t_test: Create Correlation Matrix from corrp inferences

In meantrix/corrP: Compute Correlations Type Analysis in Parallel

Create Correlation Matrix from corrp inferences

Description

Performs a distance correlation t-test of multivariate independence, based on the distance correlation t-statistic introduced by Székely and Rizzo (2013). This implementation executes the statistical approach of energy::dcorT.test, but is written in C++ for improved performance. The function supports testing for dependence between multivariate random vectors and uses a t-distribution approximation under the null hypothesis of independence. Empirical benchmarks indicate that this C++ version can be significantly faster than the original R version in the energy package, especially for larger sample sizes (e.g., 1.5–3x faster for n = 10,000).

Usage

dcor_t_test(x, y)

Arguments

x	[data.frame | matrix] Data of the first sample.
y	[data.frame | matrix] Data of the second sample.

Value

[list]
returns a list containing:

method	description of test.
statistic	observed value of the test statistic.
parameter	degrees of freedom.
estimate	bias corrected squared measure of distance correlation between x and y.
p.value	p-value of the t-test.
data.name	description of data.

References

Székely, G. J., & Rizzo, M. L. (2013). The distance correlation t-test of independence in high dimension. Journal of Multivariate Analysis, 117, 193–213. URL: https://doi.org/10.1016/j.jmva.2013.02.012. Székely, G. J., & Rizzo, M. L. (2014). Energy statistics: A class of statistics based on distances. Journal of Statistical Planning and Inference, 143(8), 1249–1272. URL: https://doi.org/10.1016/j.jspi.2013.03.018.

Examples

dcor_t_test(iris[, "Petal.Length"], iris[, c("Sepal.Length", "Sepal.Width")])

meantrix/corrP documentation built on June 12, 2025, 5:33 p.m.