# dcEvaluate

From dismo v1.3-3
by Robert Hijmans

##### Evaluate by distance class

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).

- Keywords
- spatial

##### 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

##### See Also

*Documentation reproduced from package dismo, version 1.3-3, License: GPL (>= 3)*

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