Hypervolume-class

Primary storage class for stochastic descriptions of hypervolumes

Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.

Benjamin Blonder

hypervolume

High Dimensional Geometry and Set Operations Using Kernel
Density Estimation, Support Vector Machines, and Convex Hulls

Hypervolume-class function

Objects can be created by calls of the form <code>new("Hypervolume", ...)</code>.

Objects from the Class

<dl class="dl-horizontal">
 <dt><code>Name</code>:</dt><dd>Object of class <code>"character"</code> ~~ the name of the hypervolume</dd>
 <dt><code>Method</code>:</dt><dd>Object of class <code>"character"</code> ~~ the method used to construct this hypervolume</dd>
 <dt><code>Data</code>:</dt><dd>Object of class <code>"matrix"</code> ~~ May be empty if the hypervolume is not associated with data (e.g. convex expectation, set operations)</dd>
 <dt><code>Dimensionality</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Dimensionality of the hypervolume</dd>
 <dt><code>Volume</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Volume of the hypervolume</dd>
 <dt><code>PointDensity</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Number of random points per unit volume</dd>
 <dt><code>Parameters</code>:</dt><dd>Object of class <code>"list"</code> ~~ List of parameters that will depend on the method used to construct the hypervolume</dd>
 <dt><code>RandomPoints</code>:</dt><dd>Object of class <code>"matrix"</code> ~~ A matrix of uniformly random points distributed within the hypervolume</dd>
 <dt><code>ValueAtRandomPoints</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ A vector of positive numbers representing the probabilty density at each random point in <code>@RandomPoints</code></dd>
 </dl>

Slots

Class <code>"Hypervolume"</code> — Hypervolume-class

<dl class='dl-horizontal'>
 <dt><code>Name</code>:</dt><dd>Object of class <code>"character"</code> ~~ the name of the hypervolume</dd>
 <dt><code>Method</code>:</dt><dd>Object of class <code>"character"</code> ~~ the method used to construct this hypervolume</dd>
 <dt><code>Data</code>:</dt><dd>Object of class <code>"matrix"</code> ~~ May be empty if the hypervolume is not associated with data (e.g. convex expectation, set operations)</dd>
 <dt><code>Dimensionality</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Dimensionality of the hypervolume</dd>
 <dt><code>Volume</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Volume of the hypervolume</dd>
 <dt><code>PointDensity</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ Number of random points per unit volume</dd>
 <dt><code>Parameters</code>:</dt><dd>Object of class <code>"list"</code> ~~ List of parameters that will depend on the method used to construct the hypervolume</dd>
 <dt><code>RandomPoints</code>:</dt><dd>Object of class <code>"matrix"</code> ~~ A matrix of uniformly random points distributed within the hypervolume</dd>
 <dt><code>ValueAtRandomPoints</code>:</dt><dd>Object of class <code>"numeric"</code> ~~ A vector of positive numbers representing the probabilty density at each random point in <code>@RandomPoints</code></dd>
 </dl>

Hypervolume-class: Class `"Hypervolume"`

Description

Arguments

Objects from the Class

Slots