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Setup values for survey parameterization

Setup_Sim_Survey.Rd

Setup values for survey parameterization

Usage

Setup_Sim_Survey(
  ObsSrvIdx_SE = array(0.2, dim = c(sim_list$n_regions, sim_list$n_yrs,
    sim_list$n_srv_fleets)),
  sim_list,
  srv_sel_input,
  srv_q_input = array(1, dim = c(sim_list$n_regions, sim_list$n_yrs,
    sim_list$n_srv_fleets, sim_list$n_sims)),
  t_srv = array(0, dim = c(sim_list$n_regions, sim_list$n_srv_fleets)),
  srv_idx_type = rep(1, sim_list$n_srv_fleets),
  comp_srvage_like = rep(0, sim_list$n_srv_fleets),
  ISS_SrvAgeComps = array(100, dim = c(sim_list$n_regions, sim_list$n_yrs,
    sim_list$n_sexes, sim_list$n_srv_fleets, sim_list$n_sims)),
  ln_SrvAge_theta = array(log(1), dim = c(sim_list$n_regions, sim_list$n_sexes,
    sim_list$n_srv_fleets)),
  ln_SrvAge_theta_agg = rep(log(1), sim_list$n_srv_fleets),
  SrvAge_corr_pars_agg = rep(0.01, sim_list$n_srv_fleets),
  SrvAge_corr_pars = array(0.01, dim = c(sim_list$n_regions, sim_list$n_sexes,
    sim_list$n_srv_fleets, 2)),
  SrvAgeComps_Type = array(2, dim = c(sim_list$n_yrs, sim_list$n_srv_fleets)),
  comp_srvlen_like = rep(0, sim_list$n_srv_fleets),
  ISS_SrvLenComps = array(100, dim = c(sim_list$n_regions, sim_list$n_yrs,
    sim_list$n_sexes, sim_list$n_srv_fleets, sim_list$n_sims)),
  ln_SrvLen_theta = array(log(1), dim = c(sim_list$n_regions, sim_list$n_sexes,
    sim_list$n_srv_fleets)),
  ln_SrvLen_theta_agg = rep(log(1), sim_list$n_srv_fleets),
  SrvLen_corr_pars_agg = rep(0.01, sim_list$n_srv_fleets),
  SrvLen_corr_pars = array(0.01, dim = c(sim_list$n_regions, sim_list$n_sexes,
    sim_list$n_srv_fleets, 2)),
  SrvLenComps_Type = array(2, dim = c(sim_list$n_yrs, sim_list$n_srv_fleets))
)

Arguments

ObsSrvIdx_SE

Survey index observation error [n_regions × n_yrs × n_srv_fleets] (default: `0.2`)

sim_list

Simulation list object from `Setup_Sim_Dim()`

srv_sel_input

Survey selectivity array [n_regions × n_yrs × n_ages × n_sexes × n_srv_fleets × n_sims] (no default, must be provided)

srv_q_input

Survey catchability array [n_regions × n_yrs × n_srv_fleets × n_sims] (default: `1`)

t_srv

Survey timing fraction [n_regions × n_srv_fleets] (default: `0`)

srv_idx_type

Vector of index types [n_srv_fleets] (default: all `1` = biomass index)

  • 0: Abundance index

  • 1: Biomass index

comp_srvage_like

Vector [n_srv_fleets] specifying likelihood for simulating age comps (default: all `0` = multinomial)

  • 0: Multinomial

  • 1: Dirichlet-Multinomial

  • 2: Logistic Normal iid

  • 3: Logistic Normal 1dar1

  • 4: Logistic Normal 2d correlation (constant by sex, 1dar1 by age)

ISS_SrvAgeComps

Input sample sizes [n_regions × n_yrs × n_sexes × n_srv_fleets × n_sims] (default: `100`)

ln_SrvAge_theta

Overdispersion parameters [n_regions × n_sexes × n_srv_fleets] (default: `log(1)`)

ln_SrvAge_theta_agg

Overdispersion parameters for aggregated comps [n_srv_fleets] (default: `log(1)`)

SrvAge_corr_pars_agg

Correlation parameters (agg.) for options 3–4 [n_srv_fleets] (default: `0.01`)

SrvAge_corr_pars

Correlation parameters [n_regions × n_sexes × n_srv_fleets x 2] (default: `0.01`)

SrvAgeComps_Type

Array [n_yrs × n_srv_fleets] (default: `2` = joint by sex, split by region)

  • 0: Aggregated

  • 1: Split by sex and region

  • 2: Joint by sex, split by region

  • 999: Not simulated

comp_srvlen_like

Vector [n_srv_fleets] specifying likelihood for simulating length comps (default: all `0` = multinomial)

  • 0: Multinomial

  • 1: Dirichlet-Multinomial

  • 2: Logistic Normal iid

  • 3: Logistic Normal 1dar1

  • 4: Logistic Normal 2d correlation (constant by sex, 1dar1 by length)

ISS_SrvLenComps

Input sample sizes [n_regions × n_yrs × n_sexes × n_srv_fleets × n_sims] (default: `100`)

ln_SrvLen_theta

Overdispersion parameters [n_regions × n_sexes × n_srv_fleets] (default: `log(1)`)

ln_SrvLen_theta_agg

Overdispersion parameters for aggregated comps [n_srv_fleets] (default: `log(1)`)

SrvLen_corr_pars_agg

Correlation parameters (agg.) for options 3–4 [n_srv_fleets] (default: `0.01`)

SrvLen_corr_pars

Correlation parameters [n_regions × n_sexes × n_srv_fleets x 2] (default: `0.01`)

SrvLenComps_Type

Array [n_yrs × n_srv_fleets] (default: `2` = joint by sex, split by region)

  • 0: Aggregated

  • 1: Split by sex and region

  • 2: Joint by sex, split by region

  • 999: Not simulated

See also

Other Simulation Setup: Setup_Sim_Biologicals(), Setup_Sim_Containers(), Setup_Sim_Dim(), Setup_Sim_Fishing(), Setup_Sim_Rec(), Setup_Sim_Tagging(), Setup_sim_env(), Simulate_Pop_Static(), run_annual_cycle(), simulation_data_to_SPoRC(), simulation_self_test()