Setup model objects for specifying recruitment module and associated processes

Usage

Setup_Mod_Rec(
  input_list,
  rec_model,
  rec_dd = NULL,
  rec_lag = 1,
  Use_h_prior = 0,
  h_prior = NULL,
  Use_Rec_prop_Prior = 0,
  Rec_prop_prior = NULL,
  do_rec_bias_ramp = 0,
  bias_year = NA,
  max_bias_ramp_fct = 1,
  sigmaR_switch = 1,
  dont_est_recdev_last = 0,
  init_age_strc = 2,
  equil_init_age_strc = 1,
  init_F_prop = 0,
  sigmaR_spec = NULL,
  InitDevs_spec = NULL,
  RecDevs_spec = NULL,
  h_spec = NULL,
  t_spawn = 0,
  sexratio_spec = "fix",
  sexratio_blocks = c(paste("none_Region_", c(1:input_list$data$n_regions), sep = "")),
  ...
)

Arguments

input_list

List containing data, parameters, and map lists used by the model.

rec_model

Character string specifying the recruitment model. Options are:

"mean_rec": Recruitment is a fixed mean value.
"bh_rec": Beverton-Holt recruitment with steepness parameter.

rec_dd

Character string specifying recruitment density dependence, options: "local", "global", or NULL.

rec_lag

Integer specifying the recruitment lag duration relative to spawning stock biomass (SSB).

Use_h_prior

Integer flag (0 or 1) indicating whether to apply a prior on steepness h.

h_prior

Data frame specifying beta prior distributions for the `h_trans` parameters. Must include the following columns: - `region`: Integer region index corresponding to the element in `h_trans` being penalized. - `mu`: Mean of the prior in normal space (used to calculate the corresponding beta distribution). - `sd`: Standard deviation of the prior in normal space. For each row, a beta distribution is scaled to the interval [0.2, 1], and the corresponding element of `h_trans` is transformed to that scale and penalized using the log-density from the beta distribution.

Use_Rec_prop_Prior

Integer flag (0 or 1) indicating whether to apply a prior on recruitment proportions.

Rec_prop_prior

Scalar or array specifying prior values for recruitment proportion parameters. If scalar, a constant uniform prior is applied across all dimensions.

do_rec_bias_ramp

Integer flag (0 or 1) indicating whether to apply a recruitment bias correction ramp.

bias_year

Numeric vector of length 4 defining the recruitment bias ramp periods:

Element 1: End year of no bias correction period.
Element 2: End year of ascending bias ramp period.
Element 3: End year of full bias correction period.
Element 4: Start year of final no bias correction period.

For example, with 65 years total, c(21, 31, 60, 64) means:

Years 1–21: No bias correction.
Years 22–31: Ascending bias correction.
Years 32–60: Full bias correction.
Years 61–63: Descending bias ramp.
Years 64–65: No bias correction.

max_bias_ramp_fct

Numeric specifying the maximum bias correction to apply to the recruitment bias ramp (should be between 0 and 1)

sigmaR_switch

Integer year indicating when sigmaR switches from early to late values (0 disables switching).

dont_est_recdev_last

Integer specifying how many of the most recent recruitment deviations to not estimate. Default is 0.

init_age_strc

Integer flag specifying initialization of initial age structure:

0: Initialize by iteration.
1: Initialize using a scalar geometric series w/o any movement in all groups (does not account for movement in all group).
2: Initialize using a matrix geometric series (accounts for movement; default).
3: Initialize using a scalar geometric series w/o any movement in only plus groups (does not account for movement in plus group).

equil_init_age_strc

Integer flag specifying how initial age structure deviations should be initialized. Default is stochastic for all ages except the recruitment age and the plus group.

0: Equilibrium initial age structure.
1: Stochastic initial age structure for all ages, except for the plus group, which follows equilibrium calculations (geometric series)
2: Stochastic initial age structure for all ages

init_F_prop

Numeric value specifying the initial fishing mortality proportion relative to mean fishing mortality for initializing age structure.

sigmaR_spec

Character string specifying estimation of recruitment variability (sigmaR):

NULL or "est_all": Estimate separate sigmaR for early and late periods.
"est_shared": Estimate one sigmaR shared across periods.
"fix": Fix both sigmaR values.
"fix_early_est_late": Fix early sigmaR, estimate late sigmaR.

InitDevs_spec

Character string specifying estimation of initial age deviations:

NULL: Estimate deviations for all ages and regions.
"est_shared_r": Estimate deviations shared across regions.
"fix": Fix all deviations.

RecDevs_spec

Character string specifying recruitment deviation estimation:

NULL: Estimate deviations for all regions and years.
"est_shared_r": Estimate deviations shared across regions (global recruitment deviations).
"fix": Fix all recruitment deviations.

h_spec

Character string specifying steepness estimation:

NULL: Estimate steepness for all regions if rec_model == "bh_rec".
"est_shared_r": Estimate steepness shared across regions.
"fix": Fix steepness values.

If rec_model == "mean_rec", steepness is fixed.

t_spawn

Numeric fraction specifying spawning timing within the year.

sexratio_spec

Character string specifying sex ratio estimation scheme:

"est_all" estimates sex ratio for all blocks and regions independently
"est_shared_r" estimates sex ratio shared across regions but varying by block
"fix" fixes all sex ratio (no estimation)

sexratio_blocks

Character vector specifying blocks of years and regions for sex ratio. Format examples:

"Block_1_Year_1-15_Region_1"
"Block_2_Year_16-terminal_Region_2"
"none_Region_3" (means no block, constant for that region; this is the default option)

...

Additional arguments specifying starting values for recruitment parameters such as ln_global_R0, Rec_prop, h, ln_InitDevs, ln_RecDevs, and ln_sigmaR.

Setup model objects for specifying recruitment module and associated processes

Usage

Arguments

See also