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dismo (version 1.0-5)

Species distribution modeling

Description

Functions for species distribution modeling, that is, predicting entire geographic distributions form occurrences at a number of sites.

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Version

Install

install.packages('dismo')

Monthly Downloads

12,778

Version

1.0-5

License

GPL (>= 3)

Maintainer

Robert Hijmans

Last Published

September 10th, 2014

Functions in dismo (1.0-5)

gbm.simplify

gbm simplify
kfold

k-fold partitioning
gbif

Data from GBIF
lookup

lookup
acaule

Solanum acaule data
Convex Hull

Convex hull model
ModelEvaluation

Class "ModelEvaluation"
pwdSample

Pair-wise distance sampling
maxent

Maxent
calc.deviance

Calculate deviance
threshold

Find a threshold
nicheEquivalency

Niche equivalency
ecolim

Ecolim model
voronoi

Voronoi polygons
Evaluation plots

Plot model evaluation data
pointValues

point values
ssb

Spatial sorting bias
evaluate

Model evaluation
gbm.step

gbm step
Geographic Distance

Geographic distance model
mahal

Mahalanobis model
density

density
gbm.interactions

gbm interactions
pairs

Pair plots
response

response plots
boxplot

Box plot of model evaluation data
plot

Plot predictor values
dcEvaluate

Evaluate by distance class
randomPoints

Random points
dismo-package

Species distribution modeling
evaluateROCR

Model testing with the ROCR package
mess

Multivariate environmental similarity surfaces (MESS)
Voronoi Hull

Voronoi hull model
geocode

Georeferencing with Google
gbm.plot

gbm plot
gbm.perspec

gbm perspective plot
Circles

Circles range
Anguilla data

Anguilla australis distribution data
Random null model

Random null model
prepareData

Prepare data for model fitting
domain

Domain
gbm.plot.fits

gbm plot fitted values
InvDistW

Inverse-distance weighted model
ecocrop

Ecocrop model
nicheOverlap

Niche overlap
bioclim

Bioclim
DistModel

Class "DistModel"
gbm.holdout

gbm holdout
gbm.fixed

gbm fixed
gmap

Get a Google map
predict

Distribution model predictions
gridSample

Stratified regular sample on a grid
biovars

bioclimatic variables