dist.diversity

This function computes all distance values between two probability density functions that are available in <code>getDistMethods</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

Jakub Nowosad

dist.diversity function

<dl><dt>x</dt>
<dd>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).</dd>
<dt>p</dt>
<dd>power of the Minkowski distance.</dd>
<dt>test.na</dt>
<dd>a boolean value indicating whether input vectors should be tested for NA values. Faster computations if <code>test.na = FALSE</code>.</dd>
<dt>unit</dt>
<dd>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></dd></dl>

Arguments

Author

Distance Diversity between Probability Density Functions — dist.diversity

<dl>

<dt>x</dt>
<dd>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).</dd>


<dt>p</dt>
<dd>power of the Minkowski distance.</dd>


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


<dt>unit</dt>
<dd>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></dd>

</dl>

dist.diversity: Distance Diversity between Probability Density Functions

Description

Usage

Arguments

Author

Examples