Stratified Random Sampling

Generates sampling points using stratified random sampling, where random samples are taken within each stratum.

Usage

ss_stratified(strata, n_per_stratum = 1L, seed = NULL)

Arguments

strata

An object of class ss_strata created by ss_stratify().

n_per_stratum

Integer, number of samples per stratum (default 1).

seed

Optional integer seed for reproducibility.

Value

An object of class ss_samples containing:

samples

An sf object with sampling points and stratum assignments.

method

Character, "stratified_random".

n_samples

Integer, total number of samples.

strata

The input strata object.

crs

The coordinate reference system.

Details

Stratified random sampling first divides the study area into strata, then takes random samples within each stratum. This ensures spatial coverage while maintaining the randomness required for design-based inference.

See also

ss_stratify(), ss_random(), ss_coverage()

Examples

if (FALSE) { # \dontrun{
library(sf)
poly <- st_polygon(list(rbind(c(0, 0), c(100, 0), c(100, 50), c(0, 50), c(0, 0))))
study_area <- st_sf(geometry = st_sfc(poly))

strata <- ss_stratify(study_area, n_strata = 20)
samples <- ss_stratified(strata, n_per_stratum = 1)
plot(samples)
} # }