jtct

Counts the number of complete observations where both a binary
outcome `y` and a binary predictor `x` equal 1. Missing values are excluded
pairwise (rows with `NA` in either `x` or `y` are ignored).

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

jtct function

<dl><dt>y</dt>
<dd>Outcome vector (binary: 0/1 or logical). Must be the same length as
`x`.</dd>
<dt>x</dt>
<dd>Predictor vector (binary: 0/1 or logical). Must be the same length
as `y`.</dd></dl>

Arguments

jtct — jtct

<dl>

<dt>y</dt>
<dd>Outcome vector (binary: 0/1 or logical). Must be the same length as
`x`.</dd>


<dt>x</dt>
<dd>Predictor vector (binary: 0/1 or logical). Must be the same length
as `y`.</dd>

</dl>

jtct: jtct

Description

Usage

Value

Arguments

Examples