run_maxent: Run maxEnt model

In ReseauBiodiversiteQuebec/sdm-pipeline: Package R intégrant les fonctions et données pour produire des Species Distribution Model (SDM) dans le contexte de la plateforme Biodiversité Québec.

Run maxEnt model

Description

Run maxEnt model

Usage

run_maxent(
  presence.bg,
  with_raster = F,
  algorithm = "maxnet",
  factors = NULL,
  predictors = NULL,
  covars = NULL,
  partition_type = "crossvalidation",
  nfolds = 5,
  orientation_block = "lat_lon",
  fc = "L",
  rm = 1,
  parallel = T,
  updateProgress = T,
  parallelType = "doParallel"
)

Arguments

presence.bg	data frame, containing presence/background, output of setup_sdm_data
with_raster	boolean, if F presence.bg must contain the predictors values.
algorithm	string, "maxnet" or "maxent.jar"
factors	character vector, name or names of categorical environmental variables.
predictors	spatRaster, environmental predictor variables. Used if with_raster = T.
covars	character vector, if with_raster = F, list of predictors variables (must match columns names in presence.bg)
partition_type	string, name of partitioning technique: "randomkfold","jackknife","block", "checkerboard1", "checkerboard2", and "none"
nfolds	int, number of folds (for "randomkfold" method)
orientation_block	string, one of "lat_lon" (default), "lon_lat", "lat_lat", or "lon_lon"
fc	vector of strings, feature classes to test, e.g. c("L", "LQ")
rm	vector of float, regularisation multiplier values to test, e.g. c(1,2,3)
parallel	boolean, if TRUE, run with parallel processing.
updateProgress	boolean, if TRUE, use shiny progress bar. This is only for use in shiny apps.
parallelType	character, either "doParallel" or "doSNOW" (default: "doSNOW") .

Value

spatial points

ReseauBiodiversiteQuebec/sdm-pipeline documentation built on June 23, 2022, 9:10 p.m.