kld_uniform

This function computes \(D_{KL}(p||q)\), where \(p\sim \text{U}(a_1,b_1)\)
and \(q\sim \text{U}(a_2,b_2)\), with \(a_2&lt;a_1&lt;b_1&lt;b_2\).

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

kld_uniform function

<dl><dt>a1, b1</dt>
<dd>Range of true uniform distribution</dd>
<dt>a2, b2</dt>
<dd>Range of approximate uniform distribution</dd></dl>

Arguments

Analytical KL divergence for two uniform distributions — kld_uniform

<dl>

<dt>a1, b1</dt>
<dd>Range of true uniform distribution</dd>


<dt>a2, b2</dt>
<dd>Range of approximate uniform distribution</dd>

</dl>

kld_uniform: Analytical KL divergence for two uniform distributions

Description

Usage

Value

Arguments

Examples