SDMTools: Species Distribution Modelling Tools: Tools for processing data associated with species distribution modelling exercises

This packages provides a set of tools for post processing the outcomes of species distribution modeling exercises. It includes novel methods for comparing models and tracking changes in distributions through time. It further includes methods for visualizing outcomes, selecting thresholds, calculating measures of accuracy and landscape fragmentation statistics, etc.. This package was made possible in part by financial support from the Australian Research Council & ARC Research Network for Earth System Science.

Install the latest version of this package by entering the following in R:
install.packages("SDMTools")
AuthorJeremy VanDerWal, Lorena Falconi, Stephanie Januchowski, Luke Shoo and Collin Storlie
Date of publication2014-08-05 12:16:01
MaintainerJeremy VanDerWal <jjvanderwal@gmail.com>
LicenseGPL (>= 3)
Version1.1-221
http://www.rforge.net/SDMTools/

View on CRAN

Man pages

accuracy: Measures of Model Accuracy

asc2dataframe: Ascii Grid Files to Dataframe and Dataframe to Ascii Grid...

asc.from.raster: Raster conversion functions for adehabitat, raster and sp...

auc: Area Under the Curve of the Reciever Operating Curve

circular.averaging: Circular Averaging based on Vector Averaging

ClassStat: Landscape Class Statistics

COGravity: Centre of Gravity or Mass calculations for spatial data

compare.matrix: Biplot Comparison of Matrices

confusion.matrix: Confusion Matrix

ConnCompLabel: Connected Components Labelling - Unique Patch Labelling

destination: Vincenty Direct Calculation of a Destination

distance: Vincenty Direct Calculation of Distance and Direction

extract.data: Spatial Join of Points with Raster Grids

getXYcoords: Computes the X and Y Coordinates of the Pixels of a Raster...

grid.area: Create a Grid of Cell Areas or Perimeters

grid.info: Grid Information from Geographic (lat lon) Projections

Istat: I Similarity Statistic for Quantifying Niche Overlap

Kappa: Kappa Statistic

lcmw: Least Cost Moving Windows Calculation

legend.gradient: Legend Gradient

omission: Measures of Accuracy

optim.thresh: Estimation of Optimal Threshold Values

PatchStat: Landscape Patch Statistics

pnt.in.poly: Point in Polygon

put.data: Spatial Join of Points with Raster Grids - replace data

quick.map: Quick Map

read.asc: ESRI ASCII Raster File Import And Export

Scalebar: Scalebar for Projected Maps

SigDiff: Identify Regions of Significant Differences

slope: Slope and aspect calculations

wt.mean: Weighted mean, variance and standard deviation calculations

ZonalStat: Landscape Zonal Statistics

Functions

accuracy Man page
as.asc Man page
asc2dataframe Man page
asc.from.raster Man page
asc.from.sp Man page
aspect Man page
auc Man page
circular.averaging Man page
ClassStat Man page
COGravity Man page
compare.matrix Man page
confusion.matrix Man page
ConnCompLabel Man page
dataframe2asc Man page
destination Man page
distance Man page
extract.data Man page
getXYcoords Man page
grid.area Man page
grid.info Man page
grid.perimeter Man page
image.asc Man page
ImageDiff Man page
Istat Man page
Kappa Man page
lcmw Man page
legend.gradient Man page
omission Man page
optim.thresh Man page
PatchStat Man page
pnt.in.poly Man page
print.asc Man page
prop.correct Man page
put.data Man page
quick.map Man page
raster.from.asc Man page
read.asc Man page
read.asc.gz Man page
Scalebar Man page
sensitivity Man page
SigDiff Man page
slope Man page
specificity Man page
sp.from.asc Man page
vector.averaging Man page
write.asc Man page
write.asc2 Man page
write.asc2.gz Man page
write.asc.gz Man page
wt.mean Man page
wt.sd Man page
wt.var Man page
ZonalStat Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.