gstat

Computes the likelihood-ratio test statistic (G statistic) from the mutual
information and the joint count of two variables:
$$G = 2 \times n \times MI,$$
where $n$ is the joint sample size and $MI$ is the mutual information.

Create sets of variables based on a mutual
information approach. In this context, a set is a collection of
distinct elements (e.g., variables) that can also be treated as a
single entity.  Mutual information, a concept from probability theory,
quantifies the dependence between two variables by expressing how much
information about one variable can be gained from observing the other.
Furthermore, you can analyze, and visualize
these sets in order to better understand the relationships among
variables.

Nicolas Leenaerts

setweaver

Building Sets of Variables in a Probabilistic Framework

Aaron Fisher

gstat function

<dl><dt>mi</dt>
<dd>Numeric scalar; the mutual information between two variables.</dd>
<dt>count</dt>
<dd>Integer scalar; the joint count (sample size) used in computing
<code>mi</code>.</dd></dl>

Arguments

gstat — gstat

<dl>

<dt>mi</dt>
<dd>Numeric scalar; the mutual information between two variables.</dd>


<dt>count</dt>
<dd>Integer scalar; the joint count (sample size) used in computing
<code>mi</code>.</dd>

</dl>

gstat: gstat

Description

Usage

Value

Arguments

Examples