Run grts sampling on BASSr results — run_grts_on

Sample sites based on the cost/benefit probabilities calculated in previous steps. Sites can be sampled with or without stratification.

Usage

run_grts_on_BASS(
  probs,
  nARUs,
  os = NULL,
  num_runs = 1,
  hex_id = NULL,
  stratum_id = NULL,
  remove_hexes = NULL,
  selection_weighting = inclpr,
  seed = NULL,
  ...
)

Arguments

probs: Data frame. Output of calculate_inclusion_probs() or full_BASS_run().
nARUs: Numeric, Data frame, Vector, or List. Number of base samples to choose. For stratification, a named vector/list of samples per stratum, or a data frame with columns n for samples, n_os for oversamples and the column matching stratum_id.
os: Numeric, Vector, or List. Over sample size (proportional) or named vector/list of number of samples per stratum. Ignored if nARUs is a data frame.
num_runs: Numeric. Number of times to draw random samples.
hex_id: Column. Identifies hexagon IDs (e.g., default hex_id).
stratum_id: Column. Identifies larger area (e.g., StudyAreaID or Province).
remove_hexes: Character Vector. Ids of hexagons to remove prior to sampling.
selection_weighting: Column. Identifies selection weightings used by the aux_var argument in spsurvey::grts(). Default is inclpr.
seed: Numeric. Random seed to use for random sampling. Seed only applies to specific sampling events (does not change seed in the environment). NULL does not set a seed.
...: Extra named arguments passed on to spsurvey::grts().

Value

If num_runs is 1, a single spsurvey object, otherwise a list of spsurvey objects.

Extra arguments

Extra named arguments for spsurvey::grts() can also be passed on via .... In particular, note that the default values for mindis (minimum distance between sites) is NULL, and maxtry (maximum attempts to try to obtain the minimum distance between sites) is 10.

Examples

d <- full_BASS_run(
  land_hex = psu_hexagons,
  num_runs = 10,
  n_samples = 3,
  costs = psu_costs)
#> ℹ Spatial object land_hex should be POINTs not POLYGONs
#> • Don't worry, I'll fix it!
#> • Assuming constant attributes and using centroids as points
#> ℹ Finished GRTS draw of 10 runs and 3 samples

# Simple selection
sel <- run_grts_on_BASS(
  probs = d,
  nARUs = 5,
  os = 0.2)

# Stratify
d <- dplyr::mutate(d, Province = c(rep("ON", 16), rep("MB", 17))) # Add Strata

# With lists...
sel <- run_grts_on_BASS(
  probs = d,
  nARUs = list("ON" = 5, "MB" = 2),
  stratum_id = Province,
  os = 0.2)

# With data frame...
sel <- run_grts_on_BASS(
  probs = d,
  nARUs = data.frame(Province = c("ON", "MB"),
                     n = c(5, 2),
                     n_os = c(1, 1)),
  stratum_id = Province)