quercus

Data for occurrences of Quercus alba and Quercus rubra based on geographic observations. Demonstration analysis of how to use hypervolumes for species distribution modeling using WorldClim data.

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

quercus function

A data frame with 3779 observations on the following 3 variables.<dl class="dl-horizontal">
 <dt><code>Species</code></dt><dd>a factor with levels <code>Quercus alba</code> <code>Quercus rubra</code></dd>
 <dt><code>Latitude</code></dt><dd>a numeric vector</dd>
 <dt><code>Longitude</code></dt><dd>a numeric vector</dd>
 </dl>

Format

Data and demo for Quercus (oak) tree distributions — quercus

A data frame with 3779 observations on the following 3 variables.<dl class='dl-horizontal'>
 <dt><code>Species</code></dt><dd>a factor with levels <code>Quercus alba</code> <code>Quercus rubra</code></dd>
 <dt><code>Latitude</code></dt><dd>a numeric vector</dd>
 <dt><code>Longitude</code></dt><dd>a numeric vector</dd>
 </dl>

quercus: Data and demo for Quercus (oak) tree distributions

Description

Usage

Arguments

Format

References

Examples