Clustered samples simulation

A simple procedure to simulate clustered points based on a two-step sampling.

Usage

clustered_sample(sarea, nsamples, nparents, radius)

Arguments

sarea

polygon. Area where samples should be simulated.

nsamples

integer. Number of samples to be simulated.

nparents

integer. Number of parents.

radius

integer. Radius of the buffer around each parent for offspring simulation.

Value

sf object with the simulated points and the parent to which each point belongs to.

Details

A simple procedure to simulate clustered points based on a two-step sampling. First, a pre-specified number of parents are simulated using random sampling. For each parent, `(nsamples-nparents)/nparents` are simulated within a radius of the parent point using random sampling.

Author

Carles Milà

Examples

# Simulate 100 points in a 100x100 square with 5 parents and a radius of 10.
library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE
library(ggplot2)

set.seed(1234)
simarea <- list(matrix(c(0,0,0,100,100,100,100,0,0,0), ncol=2, byrow=TRUE))
simarea <- sf::st_polygon(simarea)
simpoints <- clustered_sample(simarea, 100, 5, 10)
simpoints$parent <- as.factor(simpoints$parent)
ggplot() +
    geom_sf(data = simarea, alpha = 0) +
    geom_sf(data = simpoints, aes(col = parent))