| mvI.test {energy} | R Documentation |
Energy Statistic Test of Independence
Description
Computes the multivariate nonparametric E-statistic and test of independence
based on independence coefficient \mathcal I_n.
Usage
mvI.test(x, y, R)
mvI(x, y)
Arguments
x |
matrix: first sample, observations in rows |
y |
matrix: second sample, observations in rows |
R |
number of replicates |
Details
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.
Value
mvI returns the statistic. mvI.test returns
a list with class
htest containing
method |
description of test |
statistic |
observed value of the test statistic |
estimate |
|
replicates |
replicates of the test statistic |
p.value |
approximate p-value of the test |
data.name |
description of data |
Note
Historically this is the first energy test of independence. The
distance covariance test dcov.test, distance correlation
dcor, and related methods are more recent (2007,2009).
The distance covariance test is faster and has different properties than
mvI.test. Both methods are based on a population independence coefficient
that characterizes independence and both tests are statistically consistent.
Author(s)
Maria L. Rizzo mrizzo@bgsu.edu and Gabor J. Szekely
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,
doi:10.1016/j.jmva.2005.10.005
See Also
indep.test
mvI.test
dcov.test
dcov