dcorT {energy} | R Documentation |
Distance correlation t-test of multivariate independence for high dimension.
dcorT.test(x, y)
dcorT(x, y)
x |
data or distances of first sample |
y |
data or distances of second sample |
dcorT.test
performs a nonparametric t-test of
multivariate independence in high dimension (dimension is close to
or larger than sample size). As dimension goes to infinity, the
asymptotic distribution of the test statistic is approximately Student t with n(n-3)/2-1
degrees of freedom and for n \geq 10
the statistic is approximately distributed as standard normal.
The sample sizes (number of rows) of the two samples must agree, and samples must not contain missing values.
The t statistic (dcorT) is a transformation of a bias corrected version of distance correlation (see SR 2013 for details).
Large values (upper tail) of the dcorT statistic are significant.
dcorT
returns the dcor t statistic, and
dcorT.test
returns a list with class htest
containing
method |
description of test |
statistic |
observed value of the test statistic |
parameter |
degrees of freedom |
estimate |
(bias corrected) squared dCor(x,y) |
p.value |
p-value of the t-test |
data.name |
description of data |
dcor.t
and dcor.ttest
are deprecated.
Maria L. Rizzo mrizzo@bgsu.edu and Gabor J. Szekely
Szekely, G.J. and Rizzo, M.L. (2013). The distance correlation t-test of independence in high dimension. Journal of Multivariate Analysis, Volume 117, pp. 193-213.
doi: 10.1016/j.jmva.2013.02.012
Szekely, G.J., Rizzo, M.L., and Bakirov, N.K. (2007),
Measuring and Testing Dependence by Correlation of Distances,
Annals of Statistics, Vol. 35 No. 6, pp. 2769-2794.
doi: 10.1214/009053607000000505
Szekely, G.J. and Rizzo, M.L. (2009),
Brownian Distance Covariance,
Annals of Applied Statistics,
Vol. 3, No. 4, 1236-1265.
doi: 10.1214/09-AOAS312
x <- matrix(rnorm(100), 10, 10)
y <- matrix(runif(100), 10, 10)
dcorT(x, y)
dcorT.test(x, y)