dcEvaluate: Evaluate by distance class

In dismo: Species Distribution Modeling

Evaluate by distance class

Description

Evaluate a model for intervals of distances to the nearest point in a reference dataset for presence data and a sample of the absence data selected to have a low spatial sorting bias (obtained with pwdSample).

Usage

dcEvaluate(p, a, reference, lonlat=TRUE, binsize=15, predp, preda, model, 
               predictors, fun=predict) 

Arguments

p	two column matrix (x, y) or (longitude/latitude) or SpatialPoints object, for point locations
a	two column matrix (x, y) or (longitude/latitude) or SpatialPoints object, for point locations
reference	as above for reference point locations to which distances are computed
lonlat	Logical. Use TRUE if the coordinates are spherical (in degrees), and use FALSE if they are planar
binsize	postive integer. How many presence points in each distance bin?
predp	p
preda	a
model	m
predictors	pr
fun	function

Value

list with Evaluation objects

Author(s)

Robert J. Hijmans

See Also

pwdSample, ssb

dismo documentation built on May 31, 2023, 6:15 p.m.