Subsample simulation for completed surveys

sight_subsample_survey() resolves names to IDs then calls the sightability API. sight_subsample_survey_id() calls the API directly using integer IDs.

Usage

sight_subsample_survey(
  species,
  spatial_focus,
  bio_year,
  analysis_unit,
  survey_type,
  model,
  proportions,
  iterations = 25L,
  seed = NULL,
  ...
)

sight_subsample_survey_id(
  species_id,
  spatial_focus,
  bio_year,
  analysis_unit_id,
  survey_type_id,
  model_id,
  proportions,
  iterations = 25L,
  seed = NULL,
  dry_run = FALSE,
  ...
)

Arguments

species

Character. Species name (name-based variant only).

spatial_focus

Character. One of "DAU", "GMU", or "SubUnit".

bio_year

Integer. Biological year.

analysis_unit

Character. Analysis unit name (name-based variant only).

survey_type

Character. Survey type name (name-based variant only).

model

Character. Model name (name-based variant only).

proportions

A data.frame with columns stratum_id (integer) and proportion (numeric, 0 < p <= 1), or a list of lists with those keys. Strata not listed default to 1.0 (fully retained).

iterations

Integer. Number of subsample iterations (1–200, default 25).

seed

Integer or NULL. Random seed for reproducibility.

...

Additional arguments passed to the underlying spdgt.auth function (e.g., verbosity, timeout).

species_id

Integer. Species identifier (ID-based variant only).

analysis_unit_id

Integer. Analysis unit identifier (ID-based variant only).

survey_type_id

Integer. Survey type identifier (ID-based variant only).

model_id

Integer. Sightability model identifier.

dry_run

If TRUE, print the HTTP request without sending it and return the request object invisibly.

Value

A named list with four elements:

original

Tibble of full-data estimates.

simulations

Tibble with one row per iteration x Demographic.

summary

Per-Demographic summary statistics.

metadata

List with simulation parameters and subunit counts.

Details

Runs a stratified subunit-level subsampling simulation on a completed survey. For each iteration, a random subset of surveyed subunits is retained per stratum and the sightability model is re-fit on the server. Returns the full-data estimate alongside iteration-level results and summary statistics.

See also

sight_fit_model() for fitting without subsampling

Examples

if (FALSE) { # \dontrun{
# Using names
sight_subsample_survey(
  species = "Mule Deer",
  spatial_focus = "DAU",
  bio_year = 2024,
  analysis_unit = "North Converse 755",
  survey_type = "Sightability",
  model = "Mule Deer",
  proportions = data.frame(stratum_id = c(1L, 2L),
                           proportion = c(0.5, 0.75)),
  iterations = 25L
)

# Using IDs
sight_subsample_survey_id(
  species_id = 1,
  spatial_focus = "DAU",
  bio_year = 2024,
  analysis_unit_id = 272,
  survey_type_id = 3,
  model_id = 1,
  proportions = data.frame(stratum_id = c(1L, 2L),
                           proportion = c(0.5, 0.75)),
  iterations = 25L,
  seed = 42L
)
} # }