| wassermann {PopGenReport} | R Documentation |
Partial Mantel tests on costdistance matrices
Description
This function implements the Causal modelling approach as suggested by Wassermann et al. 2010 and Cushman et al. 2010. It tests for the effect of landscape features using a cost distance matrix on the genetic structure of subpopulation/individuals.
Usage
wassermann(gen.mat, cost.mats, eucl.mat = NULL, plot = TRUE, nperm = 999)
Arguments
gen.mat |
pairwise genetic distance matrix |
cost.mats |
pairwise cost distance matrix |
eucl.mat |
pairwise Eukclidean distance matrix |
plot |
switch for control plots of the partial mantel test |
nperm |
number of permutations for the partial mantel test |
Details
see landgenreport
Value
A table with the results of the partial mantel test. Using plot=TRUE results in diagnostic plots for the partial mantel tests.
Author(s)
Bernd Gruber (bernd.gruber@canberra.edu.au)
References
Wassermann, T.N., Cushman, S. A., Schwartz, M. K. and Wallin, D. O. (2010). Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho. Landscape Ecology, 25(10), 1601-1612.
See Also
popgenreport, genleastcost,
landgenreport, lgrMMRR
Examples
library(raster)
fric.raster <- readRDS(system.file("extdata","fric.raster.rdata", package="PopGenReport"))
glc <- genleastcost(landgen, fric.raster, "D", NN=8)
wassermann(eucl.mat = glc$eucl.mat, cost.mats = glc$cost.mats, gen.mat = glc$gen.mat)