sim_survey_parallel function

Simulate stratified random surveys using parallel computation

This function is a wrapper for sim_survey except it allows for many more total iterations to be run than sim_survey before running into RAM limitations. Unlike test_surveys, this function retains the full details of the survey and it may therefore be more useful for testing alternate approaches to a stratified analysis for obtaining survey indices.

sim_survey_parallel(
  sim,
  n_sims = 1,
  n_loops = 100,
  cores = 1,
  quiet = FALSE,
  ...
)

Arguments

• sim: Simulation from sim_distribution

• n_sims: Number of times to simulate a survey over the simulated population. Requesting a large number of simulations here may max out your RAM.

• n_loops: Number of times to run the sim_survey function. Total simulations run will be the product of n_sims and n_loops

  arguments. Low numbers of n_sims and high numbers of n_loops

  will be easier on RAM, but may be slower.

• cores: Number of cores to use in parallel. More cores should speed up the process.

• quiet: Print message on what to expect for duration?

• ...: Arguments passed on to sim_survey

  • q: Closure, such as sim_logistic, for simulating catchability at age (returned values must be between 0 and 1)

  • trawl_dim: Trawl width and distance (same units as grid)

  • resample_cells: Allow resampling of sampling units (grid cells)? Setting to TRUE may introduce bias because depletion is imposed at the cell level.

  • binom_error: Impose binomial error? Setting to FALSE may introduce bias in stratified estimates at older ages because of more frequent rounding to zero.

  • min_sets: Minimum number of sets per strat

  • set_den: Set density (number of sets per grid unit squared). WARNING: may return an error if set_den is high and resample_cells = FALSE because the number of sets allocated may exceed the number of cells in a strata.

  • lengths_cap: Maximum number of lengths measured per set

  • ages_cap: If age_sampling = "stratified", this cap represents the maximum number of ages to sample per length group (defined using the age_length_group

     argument) per division or strat (defined using the `age_space_group` argument) per year. If `age_sampling = "random"`, it is the maximum number of ages to sample from measured fish per set.
    

  • age_sampling: Should age sampling be "stratified" (default) or "random"?

  • age_length_group: Numeric value indicating the size of the length bins for stratified age sampling. Ignored if age_sampling = "random".

  • age_space_group: Should age sampling occur at the "division" (default), "strat" or "set" spatial scale? That is, age sampling can be spread across each "division", "strat" or "set" in each year to a maximum number within each length bin (cap is defined using the age_cap argument). Ignored if age_sampling = "random".

  • custom_sets: Supply an object of the same structure as returned by sim_sets which specifies a custom series of set locations to be sampled. Set locations are automated if custom_sets = NULL.

  • light: Drop some objects from the output to keep object size low?

Returns

Returns an object of the same structure as sim_survey.

Details

sim_survey is hard-wired here to be "light" to minimize object size.

Examples

## This call runs a total of 25 simulations of the same survey over
## the same population (Note: total number of simulations are low to
## decrease computation time for the example)
sim <- sim_abundance(ages = 1:20, years = 1:5) %>%
           sim_distribution(grid = make_grid(res = c(10, 10))) %>%
           sim_survey_parallel(n_sims = 5, n_loops = 5, cores = 1,
                               q = sim_logistic(k = 2, x0 = 3),
                               quiet = FALSE)