dist.diversity

a numeric <code>data.frame</code> or <code>matrix</code> (storing probability vectors) or a numeric <code>data.frame</code> or <code>matrix</code> storing counts (if <code>est.prob</code> is specified).

a boolean value indicating whether input vectors should be tested for NA values. Faster computations if <code>test.na = FALSE</code>.

test.na

a character string specifying the logarithm unit that should be used to compute distances that depend on log computations. Options are:<ul>
<li><code>unit = "log"</code></li>
<li><code>unit = "log2"</code></li>
<li><code>unit = "log10"</code></li>
</ul>

unit

This function computes all distance values between two probability density functions that are available in <code><a rd-options="" href="/link/getDistMethods?package=philentropy&version=0.5.0" data-mini-rdoc="philentropy::getDistMethods">getDistMethods</a></code>
and returns a vector storing the corresponding distance measures. This vector is named distance diversity vector.

Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.

Hajk-Georg Drost

philentropy

Similarity and Distance Quantification Between Probability
Functions

dist.diversity function

This function computes all distance values between two probability density functions that are available in <code><a rd-options='' href='getDistMethods'>getDistMethods</a></code>
and returns a vector storing the corresponding distance measures. This vector is named distance diversity vector.

dist.diversity: Distance Diversity between Probability Density Functions

Description

Usage

Arguments

Examples