EVnormal

eigenvalues

Pre-computed eigenvalues corresponding to the asymptotic sampling
 distribution of the energy test statistic for univariate
 normality, under the null hypothesis. Four Cases are computed:<ol>
<li>Simple hypothesis, known parameters.</li>
<li>Estimated mean, known variance.</li>
<li>Known mean, estimated variance.</li>
<li>Composite hypothesis, estimated parameters.</li>
</ol>Case 4 eigenvalues are used in the test function <code>normal.test</code>
when <code>method=="limit"</code>.

E-statistics (energy) tests and statistics for multivariate and univariate inference,
including distance correlation, one-sample, two-sample, and multi-sample tests for
comparing multivariate distributions, are implemented. Measuring and testing
multivariate independence based on distance correlation, partial distance correlation,
multivariate goodness-of-fit tests, k-groups and hierarchical clustering based on energy
distance, testing for multivariate normality, distance components (disco) for non-parametric
analysis of structured data, and other energy statistics/methods are implemented.

Maria Rizzo

energy

E-Statistics: Multivariate Inference via the Energy of Data

Gabor Szekely

EVnormal function

Numeric matrix with 125 rows and 5 columns;
 column 1 is the index, and columns 2-5 are 
 the eigenvalues of Cases 1-4.

EVnormal: Eigenvalues for the energy Test of Univariate Normality

Description

Usage

Arguments

Format

References