energy (version 1.6.2)

indep.etest: Energy Statistic Test of Independence

Description

Deprecated: use indep.test with method = mvI. Computes a multivariate nonparametric E-statistic and test of independence.

Usage

indep.e(x, y)
indep.etest(x, y, R=199)

Arguments

x

matrix: first sample, observations in rows

y

matrix: second sample, observations in rows

R

number of replicates

Value

The sample coefficient $I$ is returned by indep.e. The function indep.etest returns a list with class htest containing

method

description of test

statistic

observed value of the coefficient $I$

p.value

approximate p-value of the test

data.name

description of data

Details

Computes the coefficient $I_n$ and performs a nonparametric $E$-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 $E = I^2$ is a ratio of V-statistics based on interpoint distances $||x_{i}-y_{j}||$. See the reference below for details.

References

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, http://dx.doi.org/10.1016/j.jmva.2005.10.005

Examples

 ## Not run: 
#  ## independent univariate data
#  x <- sin(runif(30, 0, 2*pi) * 2)
#  y <- sin(runif(30, 0, 2*pi) * 4)
#  indep.etest(x, y, R = 99)
#  
#  ## dependent multivariate data
#  Sigma <- matrix(c(1, .1, 0, 0 , 1, 0, 0 ,.1, 1), 3, 3)
#  x <- mvrnorm(30, c(0, 0, 0), diag(3))
#  y <- mvrnorm(30, c(0, 0, 0), Sigma) * x
#  indep.etest(x, y, R = 99)
#  ## End(Not run)