clustered_sample {CAST} | R Documentation |
A simple procedure to simulate clustered points based on a two-step sampling.
clustered_sample(sarea, nsamples, nparents, radius)
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. |
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.
sf object with the simulated points and the parent to which each point belongs to.
Carles MilĂ
# Simulate 100 points in a 100x100 square with 5 parents and a radius of 10.
library(sf)
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))