montecarlo_gcms: Perform Monte Carlo Permutations on GCMs

In chooseGCM: Selecting General Circulation Models for Species Distribution Modeling

Perform Monte Carlo Permutations on GCMs

Description

This function performs Monte Carlo permutations on a distance matrix and produces a violin plot showing the mean distance between subsets of the distance matrix.

Usage

montecarlo_gcms(
  s,
  var_names = c("bio_1", "bio_12"),
  study_area = NULL,
  scale = TRUE,
  perm = 10000,
  dist_method = "euclidean",
  clustering_method = "closestdist",
  ...
)

Arguments

s	A list of stacks of General Circulation Models (GCMs).
var_names	Character. A vector of names of the variables to include, or 'all' to include all variables.
study_area	An Extent object, or any object from which an Extent object can be extracted. Defines the study area for cropping and masking the rasters.
scale	Logical. Should the data be centered and scaled? Default is TRUE.
perm	Integer. The number of permutations to perform.
dist_method	Character. The method for distance matrix computation. Default is "euclidean." Possible values are: "euclidean," "maximum," "manhattan," "canberra," "binary," or "minkowski." If NULL, clustering will be performed on the raw variable data.
clustering_method	Character. The method for clustering. Default is "closestdist." Possible values are: "kmeans," "hclust," or "closestdist."
...	Additional arguments to pass to the clustering function.

Value

A violin plot showing the results. The dashed red line and red dots represent the mean absolute distance between subsets of GCMs using the clustering approach. The violin plot is generated from Monte Carlo permutations, selecting random subsets of GCMs from the provided set.

Author(s)

Luíz Fernando Esser ([e-mail]) https://luizfesser.wordpress.com

See Also

hclust_gcms env_gcms kmeans_gcms

Examples

var_names <- c("bio_1", "bio_12")
s <- import_gcms(system.file("extdata", package = "chooseGCM"), var_names = var_names)
study_area <- terra::ext(c(-80, -30, -50, 10)) |> terra::vect(crs="epsg:4326")
montecarlo_gcms(s, var_names, study_area)

chooseGCM documentation built on April 3, 2025, 5:27 p.m.