ML_ex_dat

A <code>dataframe</code> containing a subset of GPS location data from 2 male and 1 female mountain lions used
for testing and running sequential cluster function examples.Example data provided by Wyoming Game and Fish Department, 2020.

datasets

Applies sequential clustering algorithm to animal location data
based on user-defined parameters. Plots interactive cluster maps and
provides a summary dataframe with attributes for each cluster commonly
used as covariates in subsequent modeling efforts. Additional functions
provide individual keyhole markup language plots for quick assessment,
and export of global positioning system exchange format files for
navigation purposes.
Methods can be found at <doi:10.1111/2041-210X.13572>.

Justin Clapp

GPSeqClus

Sequential Clustering Algorithm for Location Data

ML_ex_dat function

A <code>dataframe</code> containing 4 columns:<dl>
<dt>AID</dt>
<dd>animal identification</dd><dt>TelemDate</dt>
<dd>location timestamp in POSIXct format</dd><dt>Lat</dt>
<dd>latitude coordinates</dd><dt>Long</dt>
<dd>longitude coordinates</dd>
</dl>

Format

Sample Data for Sequential Clustering Routine — ML_ex_dat

A <code>dataframe</code> containing 4 columns:<dl>
<dt>AID</dt>
<dd>animal identification</dd>

<dt>TelemDate</dt>
<dd>location timestamp in POSIXct format</dd>

<dt>Lat</dt>
<dd>latitude coordinates</dd>

<dt>Long</dt>
<dd>longitude coordinates</dd>


</dl>

ML_ex_dat: Sample Data for Sequential Clustering Routine

Description

Usage

Arguments

Format