GeNetIt is an R package for spatial graph-theoretic gravity modeling. The model framework is applicable for other types of matrix-based spatial flow (from-to) problems. Includes functions for constructing spatial graphs, sampling, summarizing associated raster variables and building unconstrained and singly constrained gravity models following Murphy et al., (2010).
As of version 0.1-6 all support of raster (RasterLayer, RasterStack) and sp (SpatialPointsDataFrame) class objects
has ended, replaced by terra (SpatRaster) and sf (sf POINT) classes.
You can access a full tutorial here
GeNetIt Function |
Description |
|---|---|
adj.matrix |
Creates binary adjacency matrix of from-to (joins) structure of graph |
build.node.data |
Build node data |
compare.models |
Compare competing hypothesis (models) |
dmatrix.df |
Distance matrix to data.frame |
dps |
dps genetic distance matrix for Columbia spotted frog (Rana luteiventris) |
flow |
Convert distance matrix to flow (1-d) |
graph.metrics |
Calculates a suite of metrics on the structure of the graph |
graph.statistics |
Raster statistics for edges (lines) with buffer argument for multi-scale assessment |
gravity.es |
Effect size for a gravity model |
gravity |
Gravity model |
knn.graph |
K Nearest Neighbor or saturated Graph |
node.statistics |
Raster statistics for nodes (points) |
plot.gravity |
plot generic for a gravity model object |
predict.gravity |
predict generic gravity model |
print.gravity |
print generic gravity model |
ralu.model |
Columbia spotted frog (Rana luteiventris) data for specifying gravity model. Note, the data.frame is already log transformed. |
ralu.site |
Subset of site-level spatial point data for Columbia spotted frog (Rana luteiventris) |
rasters |
Subset of raster data for Columbia spotted frog (Rana luteiventris) |
summary.gravity |
summary generic for gravity model objects |
area.graph.statistics |
Depreciated, please use graph.statistics with buffer argument |
Bugs: Users are encouraged to report bugs here. Go to issues in the menu above, and press new issue to start a new bug report, documentation correction or feature request. You can direct questions to [email protected].
To install GeNetIt in R use install.packages() to download curent stable release from CRAN
or, for the development version, run the following (requires the remotes package):
remotes::install_github("jeffreyevans/GeNetIt")