clustered_sample: Clustered samples simulation

In CAST: 'caret' Applications for Spatial-Temporal Models

Clustered samples simulation

Description

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.

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.

Value

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

Author(s)

Carles Milà

Examples

# 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))

CAST documentation built on June 22, 2024, 10:47 a.m.