Run Retrospective Diagnostics for RTMB Models

Refits the model with terminal years removed one peel at a time, truncating the inputs, applying any data lags and Francis reweighting, and extracting spawning stock biomass and recruitment from each fit.

Usage

do_retrospective(
  n_retro,
  data,
  parameters,
  mapping,
  random = NULL,
  do_par,
  n_cores,
  newton_loops = 3,
  do_francis = FALSE,
  n_francis_iter = NULL,
  nlminb_control = list(iter.max = 1e+05, eval.max = 1e+05, rel.tol = 1e-15),
  do_sdrep = FALSE,
  fishidx_datalag = array(0, dim = c(data$n_regions, data$n_fish_fleets)),
  fishage_datalag = array(0, dim = c(data$n_regions, data$n_fish_fleets)),
  fishlen_datalag = array(0, dim = c(data$n_regions, data$n_fish_fleets)),
  fishage_discard_datalag = array(0, dim = c(data$n_regions, data$n_fish_fleets)),
  fishlen_discard_datalag = array(0, dim = c(data$n_regions, data$n_fish_fleets)),
  srvidx_datalag = array(0, dim = c(data$n_regions, data$n_srv_fleets)),
  srvage_datalag = array(0, dim = c(data$n_regions, data$n_srv_fleets)),
  srvlen_datalag = array(0, dim = c(data$n_regions, data$n_srv_fleets)),
  fishidx_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_fish_fleets)),
  fishage_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_fish_fleets)),
  fishlen_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_fish_fleets)),
  fishage_discard_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions,
    data$n_fish_fleets)),
  fishlen_discard_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions,
    data$n_fish_fleets)),
  srvidx_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_srv_fleets)),
  srvage_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_srv_fleets)),
  srvlen_pop_datalag = array(0, dim = c(data$n_pop, data$n_regions, data$n_srv_fleets)),
  conv_tag_datalag = 0,
  return_models = FALSE
)

Arguments

n_retro: Number of peels. 0 fits the full dataset only.
data: List of data supplied to the RTMB model.
parameters: List of model parameters.
mapping: List of parameter mappings used during estimation.
random: Character vector of random-effect parameters. Default NULL.
do_par: Logical, whether the peels run in parallel. Default FALSE.
n_cores: Cores used when do_par = TRUE.
newton_loops: Newton optimization loops per fit. Default 3.
do_francis: Logical, whether Francis reweighting runs within each peel. Default FALSE.
n_francis_iter: Francis reweighting iterations, required when do_francis = TRUE.
nlminb_control: Control list passed to stats::nlminb. Default list(iter.max = 1e5, eval.max = 1e5, rel.tol = 1e-15).
do_sdrep: Logical, whether standard errors are computed through RTMB::sdreport. Default FALSE.
fishidx_datalag, fishage_datalag, fishlen_datalag, fishage_discard_datalag, fishlen_discard_datalag, srvidx_datalag, srvage_datalag, srvlen_datalag: Integer arrays \([region \times fleet]\) of the lag applied to each pooled data source. Default zeros.
fishidx_pop_datalag, fishage_pop_datalag, fishlen_pop_datalag, fishage_discard_pop_datalag, fishlen_discard_pop_datalag, srvidx_pop_datalag, srvage_pop_datalag, srvlen_pop_datalag: The population-specific counterparts, \([n\_pop \times region \times fleet]\). Default zeros.
conv_tag_datalag: Integer lag applied to the conventional tagging data. Default 0.
return_models: Logical, whether the fitted objects are returned per peel. Default FALSE. TRUE returns a list of retro_df and retro_models, the latter indexed peel_0, peel_1 and so on.

Value

A long-format data frame of retrospective spawning stock biomass and recruitment, with columns Pop, Region, Year, Type ("SSB" or "Recruitment"), peel (0 for the full data), and value. Under do_sdrep = TRUE it also holds pdHess and max_grad, the maximum absolute gradient of the fixed effects.

Usage

Arguments

Value

See also