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
Available functions in GeNetIt 0.1-6 are: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 jeffrey_evans@tnc.org.
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")
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