Computes the multivariate nonparametric E-statistic and test of independence based on independence coefficient \(\mathcal I_n\).
mvI.test(x, y, R)
mvI(x, y)mvI returns the statistic. mvI.test returns
a list with class
htest containing
description of test
observed value of the test statistic \(n\mathcal I_n^2\)
\(\mathcal I_n\)
replicates of the test statistic
approximate p-value of the test
description of data
matrix: first sample, observations in rows
matrix: second sample, observations in rows
number of replicates
Maria L. Rizzo mrizzo@bgsu.edu and Gabor J. Szekely
Computes the coefficient \(\mathcal I\) and performs a nonparametric
\(\mathcal E\)-test of independence. The test decision is obtained via
bootstrap, with R replicates.
The sample sizes (number of rows) of the two samples must agree, and
samples must not contain missing values. The statistic
\(\mathcal E = n \mathcal I^2\) is a ratio of V-statistics based
on interpoint distances \(\|x_{i}-y_{j}\|\).
See the reference below for details.
Bakirov, N.K., Rizzo, M.L., and Szekely, G.J. (2006), A Multivariate
Nonparametric Test of Independence, Journal of Multivariate Analysis
93/1, 58-80,
tools:::Rd_expr_doi("10.1016/j.jmva.2005.10.005")
indep.test
mvI.test
dcov.test
dcov