optk_gcms: Optimize the number of clusters for a dataset

In chooseGCM: Selecting General Circulation Models for Species Distribution Modeling

Optimize the number of clusters for a dataset

Description

This function performs clustering analysis on a dataset and determines the optimal number of clusters based on a specified method.

Usage

optk_gcms(
  s,
  var_names = c("bio_1", "bio_12"),
  study_area = NULL,
  cluster = "kmeans",
  method = "wss",
  n = NULL,
  nstart = 10,
  K.max = 10,
  B = 100
)

Arguments

s	A list of stacks of General Circulation Models.
var_names	Character. A vector with the names of the variables to compare OR 'all'.
study_area	Extent object, or any object from which an Extent object can be extracted. An object that defines the study area for cropping and masking the rasters.
cluster	A character string specifying the method to build the clusters. Options are 'kmeans' (default) or 'hclust'.
method	A character string specifying the method to use for determining the optimal number of clusters. Options are 'wss' for within-cluster sum of squares, 'silhouette' for average silhouette width, and 'gap_stat' for the gap statistic method. Default is 'wss'.
n	An integer specifying the number of randomly selected samples to use in the clustering analysis. If NULL (default), all data is used.
nstart	Numeric. The number of random sets to be chosen. Default is 10. Argument is passed to 'stats::kmeans()'.
K.max	Numeric. The maximum number of clusters to consider. Default is 10. Argument is passed to 'factoextra::fviz_nbclust()'.
B	Integer. The number of Monte Carlo (“bootstrap”) samples. Default is 100. Argument is passed to 'cluster::clusGap()'.

Value

A ggplot object representing the optimal number of clusters.

Author(s)

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

See Also

transform_gcms flatten_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")
optk_gcms(s, var_names, study_area)

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