matie-package: Measuring Association and Testing Independence Efficiently

In matie: Measuring Association and Testing Independence Efficiently

Description

A non-parametric measure of association between variables. The association score, A, ranges from 0 (when the variables are independent) to 1 (when they are perfectly associated). A is a kind of R^2 estimate, and can be thought of as the proportion of variance in one variable explained by another (or explained by a number of other variables - A works for multivariate associations as well).

matie computes A by estimating a generalized R^2, which is computed from the ratio of the likelihood of an alternative model (allowing dependence between variables) over the likelihood of a null model (that forces the variables to be independent). See http://arxiv.org/abs/1303.1828 for details.

The variables should be continuous. A is calculated from the ranks of the values, and ties are currently broken randomly. Ordinal data can be handled, but the properties of A have not been thoroughly investigated for non-continuous data with many ties. A is not currently implemented for category-valued data.

Version 1.2 provides underflow protection to fix a bug that appeared at high dimensions in earlier versions.

Details

Package:	matie
Type:	Package
Version:	1.2
Date:	2013-10-11
License:	GPL-3

Author(s)

Ben Murrell, Dan Murrell, Hugh Murrell. Maintainer: Hugh Murrell <[e-mail]>

References

Discovering general multidimensional associations, http://arxiv.org/abs/1303.1828

Examples

    d <- sbd(NULL,n=400,Rsq=0.9)
    aScore <- ma(d)
    pValue <- ma.test(d,aScore)

matie documentation built on May 2, 2019, 3:52 a.m.