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?

Value

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

# \donttest{
## 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)
#> One run of sim_survey took ~ 1 secs to run. It may take up to 8 secs to run all simulations.
# }