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dismo (version 1.0-12)
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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Install
install.packages('dismo')
Monthly Downloads
10,019
Version
1.0-12
License
GPL (>= 3)
Maintainer
Robert Hijmans
Last Published
March 15th, 2015
Functions in dismo (1.0-12)
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gbm.step
gbm step
Anguilla data
Anguilla australis distribution data
Voronoi Hull
Voronoi hull model
Convex Hull
Convex hull model
mahal
Mahalanobis model
threshold
Find a threshold
nicheOverlap
Niche overlap
calc.deviance
Calculate deviance
maxent
Maxent
dismo-package
Species distribution modeling
pointValues
point values
evaluateROCR
Model testing with the ROCR package
nicheEquivalency
Niche equivalency
prepareData
Prepare data for model fitting
gmap
Get a Google map
DistModel
Class "DistModel"
gbif
Data from GBIF
Geographic Distance
Geographic distance model
Circles
Circles range
gbm.interactions
gbm interactions
ModelEvaluation
Class "ModelEvaluation"
pwdSample
Pair-wise distance sampling
dcEvaluate
Evaluate by distance class
acaule
Solanum acaule data
gbm.simplify
gbm simplify
kfold
k-fold partitioning
gbm.plot.fits
gbm plot fitted values
gbm.plot
gbm plot
randomPoints
Random points
gbm.perspec
gbm perspective plot
evaluate
Model evaluation
gbm.fixed
gbm fixed
boxplot
Box plot of model evaluation data
ecolim
Ecolim model
plot
Plot predictor values
geocode
Georeferencing with Google
biovars
bioclimatic variables
density
density
Random null model
Random null model
voronoi
Voronoi polygons
ecocrop
Ecocrop model
response
response plots
ssb
Spatial sorting bias
bioclim
Bioclim
predict
Distribution model predictions
Evaluation plots
Plot model evaluation data
gbm.holdout
gbm holdout
mess
Multivariate environmental similarity surfaces (MESS)
domain
Domain
gridSample
Stratified regular sample on a grid
InvDistW
Inverse-distance weighted model
pairs
Pair plots