thin.algorithm: Implements random spatial thinning algorithm

In spThin: Functions for Spatial Thinning of Species Occurrence Records for Use in Ecological Models

Description

thin.algorithm implements a randomization approach to spatially thinning species occurence data. This function is the algorithm underlying the thin function.

Usage

thin.algorithm(rec.df.orig, thin.par, reps)

Arguments

rec.df.orig	A data frame of long/lat points for each presence record. The data.frame should be a two-column data frame, one column of long and one of lat
thin.par	Thinning parameter - the distance (in kilometers) that you want records to be separated by.
reps	The number of times to repete the thinning process. Given the random process of removing nearest-neighbors there should be 'rep' number of different sets of coordinates.

Value

reduced.rec.dfs: A list object of length 'rep'. Each list element is a different data.frame of spatially thinned presence records.

spThin documentation built on Nov. 16, 2019, 1:07 a.m.