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GDM function to do everything (fit model, get coefficients, make and save raster)

gdm_do_everything.Rd

GDM function to do everything (fit model, get coefficients, make and save raster)

Usage

gdm_do_everything(
  gendist,
  coords,
  envlayers = NULL,
  env = NULL,
  model = "full",
  sig = 0.05,
  nperm = 50,
  geodist_type = "Euclidean",
  dist_lyr = NULL,
  scale_gendist = FALSE,
  plot_vars = TRUE,
  quiet = FALSE
)

Arguments

gendist

matrix of genetic distances (must range between 0 and 1 or set scale_gendist = TRUE)

coords

dataframe with x (i.e., longitude) and y (i.e., latitude) coordinates; must be in this order

envlayers

SpatRaster or Raster* object for mapping (if env`` is provided, the dataframe column names and envlayers`` layer names should be the same)

env

dataframe or raster object with environmental values for each coordinate; if not provided, it will be calculated based on coords/envlayers

model

whether to fit the model with all variables ("full") or to perform variable selection to determine the best set of variables ("best"); defaults to "full"

sig

alpha value for significance threshold (defaults to 0.05); only used if model = "best"

nperm

number of permutations to use to calculate variable importance; only used if model = "best" (defaults to 50)

geodist_type

the type of geographic distance to be calculated; options are "Euclidean" (default) for direct distance, "topographic" for topographic distances, and "resistance" for resistance distances. Note: creation and plotting of the GDM raster is only possible for "Euclidean" distances

dist_lyr

DEM raster for calculating topographic distances or resistance raster for calculating resistance distances

scale_gendist

whether to scale genetic distance data from 0 to 1 (defaults to FALSE)

plot_vars

whether to create PCA plot to help in variable and map interpretation (defaults to TRUE)

quiet

whether to operate quietly and suppress the output of tables and figures (defaults to FALSE)

Value

list with final model, predictor coefficients, and PCA RGB map

Details

GDM is run using the gdm package: Fitzpatrick, M., Mokany, K., Manion, G., Nieto-Lugilde, D., & Ferrier, S. (2022). gdm: Generalized dissimilarity modeling. R package version 1.5.0-3.

See also

Other GDM functions: gdm_coeffs(), gdm_df(), gdm_format(), gdm_map(), gdm_plot_diss(), gdm_plot_isplines(), gdm_plot_vars(), gdm_run(), gdm_table(), gdm_var_sel(), scale01()