Survey input sample size function — srvy

Bootstrap data sources to replicate bottom trawl survey age and length composition for computation of input sample size

srvy_iss(
  iters = 1,
  lfreq_data,
  specimen_data,
  cpue_data,
  strata_data,
  yrs = NULL,
  bin = 1,
  boot_hauls = FALSE,
  boot_lengths = FALSE,
  boot_ages = FALSE,
  al_var = FALSE,
  al_var_ann = FALSE,
  age_err = FALSE,
  len_samples = NULL,
  age_samples = NULL,
  plus_len = NULL,
  plus_age = NULL,
  by_strata = FALSE,
  global = FALSE,
  region = "goa",
  save_interm = FALSE,
  save_stats = FALSE,
  save
)

Arguments

iters: number of iterations (min of 500 recommended for full run)
lfreq_data: length frequency input dataframe
specimen_data: age-length specimen input dataframe
cpue_data: catch-per-unit effort input dataframe
strata_data: strata id and area size input dataframe
yrs: any year filter >= (default = NULL)
bin: bin size (default = 1 cm), also can use custom length bins following ss3 bin convention
boot_hauls: Boolean. Resample hauls w/replacement? (default = FALSE)
boot_lengths: Boolean. Resample length frequency w/replacement? (default = FALSE)
boot_ages: Boolean. Resample ages w/replacement? (default = FALSE)
al_var: Boolean. Include age-length variability in resampled age data? (default = FALSE)
al_var_ann: Boolean. Resample age-length variability annually or pooled across years? (default = FALSE)
age_err: Boolean. Include ageing error in resampled age data? (default = FALSE)
len_samples: If set at a value, tests reductions in haul-level length sampling. To test, set this value at some smaller level than current sampling rate, i.e., 25 (default = NULL)
age_samples: If set at a value, tests reductions (and increases) in survey-level number of ages collected. To test, set at a proportion of ages collected, i.e., 0.8 or 1.2 (default = NULL)
plus_len: If set at a value, computes length expansion with a plus-length group (default = FALSE)
plus_age: If set at a value, computes age expansion with a plus-age group (default = FALSE)
by_strata: Boolean. Should length/age pop'n values be computed at stratum level? (default = FALSE)
global: Boolean. Fill in missing length bins with global age-lenth key? (default = FALSE)
region: Region will create a folder and place results in said folder. (default = 'goa')
save_interm: Boolean. Save the intermediate results: resampled age/length comps and realized sample size per iteration? (default = FALSE)
save_stats: Boolean. Save other statistics: base age/length comps without resampling, mean length-at-age, bootstrap bias? (default = FALSE)
save: Name to attach to and identify output files.

Value

Dataframe of input sample size by year, species (using RACE species codes), sex (0 - combined sex with age/length data combined prior to expansion, 1 - males, 2 - females, 3 - unsexed, 12 - female/male compositions that sum to one across both sexes combined, 4 - combined sex after summing sex-specific age/length composition after expansion; all with short description IDs in sex_desc column) for age composition (output saved with 'iss_age' in file name) and length composition (output saved with 'iss_ln' in file name). For comparison, nominal sample size ('nss' - the number of age/length samples actually taken) and the number of sampled hauls for age/length ('nhls') are included. Will also produce other dataframes if desired (see save_intern and save_stats argument descriptions).