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Generate ellipses via multivariate normal biased sampling

Source: R/virtual_comunities.R
conserved_ellipses.Rd

Creates a set of ellipses with centroids sampled from a background, biased by their proximity to the centroid to a reference niche. Includes an option to thin the background to reduce centroid sampling bias due to point-density.

Usage

conserved_ellipses(
  object,
  background,
  n = 10,
  smallest_proportion = 0.1,
  largest_proportion = 1,
  thin_background = FALSE,
  resolution = 100,
  seed = 1
)

Arguments

object

A nicheR_ellipsoid object used as the reference. This is will be considered the "largest" ellipse to be generated.

background

Matrix or Dataframe. The 2D point cloud (coordinates) used to select centroids for the ellipses.

n

Integer. Number of ellipses to generate. Default = 10.

smallest_proportion

Numeric scalar in (0, 1). The scale of the smallest ellipse relative to the original. Default is 0.1.

largest_proportion

Numeric. Maximum scaling factor for the variance relative to the reference. Default = 1.0. This controls how much larger the new ellipses can be compared to the reference. Values larger than 1 will result in ellipses that exceed the reference size.

thin_background

Logical. If TRUE, centroids are sampled more uniformly across the background using a grid-based thinning approach. Default = FALSE.

resolution

Integer. Number of cells per side in the grid to deal with point density variation across background. Default = 100.

seed

Integer. Random seed for reproducibility. Default = 1. Set to NULL for no seeding.

Value

An object of class nicheR_community containing the generated ellipses, the reference object, and generation metadata.

Details

Ellipses are generated to simulate a community of niches with varying degrees of similarity to the reference. The distribution of the generated ellipses is influenced by the proximity to the reference and the density of the background points.