is_two_sample

Detect if a one- or two-sample problem is specified

Estimation algorithms for Kullback-Leibler divergence between two probability
distributions, based on one or two samples, and including uncertainty quantification.
Distributions can be uni- or multivariate and continuous, discrete or mixed.

Niklas Hartung

kldest

Sample-Based Estimation of Kullback-Leibler Divergence

is_two_sample function

<dl><dt>Y</dt>
<dd>A vector, matrix, data frame or <code>NULL</code></dd>
<dt>q</dt>
<dd>A function or <code>NULL</code>.</dd></dl>

Arguments

Detect if a one- or two-sample problem is specified — is_two_sample

<dl>

<dt>Y</dt>
<dd>A vector, matrix, data frame or <code>NULL</code></dd>


<dt>q</dt>
<dd>A function or <code>NULL</code>.</dd>

</dl>

is_two_sample: Detect if a one- or two-sample problem is specified

Description

Usage

Value

Arguments