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usdm

Uncertainty Analysis for Species Distribution Modelling

The usdm package provides a set of functions to support dealing with problematic situations in species distribution modelling (e.g., multicollinearity, positional uncertainty).

To detect whether predictor variables are subjected to multicollinearity, you may use vif (variance inflation factor) metric, and some methods implemeted in this package including vifstep or vifcor (a stepwise procedure to identify collinear variables).

To detect whether positional uncertainty in species data may affect SDMs, different strategies are implemented through using either global or local spatial autocorrelation. You may check the following links for more information:

https://r-gis.net/?q=positional_uncertainty (using global spatial autocorrelation)

https://r-gis.net/?q=positional_uncertainty2 (using local spatial autocorrelation)

To develop species distribution models (SDMs), you may use the sdm package.

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Version

Install

install.packages('usdm')

Monthly Downloads

1,962

Version

2.1-7

License

GPL (>= 3)

Maintainer

Last Published

September 29th, 2023

Functions in usdm (2.1-7)

speciesLISA-class

speciesLISA class
usdm-package

Uncertainty analysis for SDMs
plot.speciesLISA

Plot positional uncertainty based on LISA
Variogram

Empirical variogram for raster data
RasterVariogram-class

RasterVariogram class
exclude

Excluding variables specified in a VIF object
vif

Variance Inflation Factor and test for multicollinearity
lisa

Local indicators of spatial association
speciesLisa

LISA in predictors at species occurrence locations
VIF-class

VIF class
plot.RasterVariogram

Plot variogram or variogram cloud or boxplot based on variogram cloud