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Run Likelihood Profile

do_likelihood_profile.Rd

Profiles the joint negative log-likelihood and all individual likelihood components across a range of fixed values for a single parameter. Supports both sequential and parallel execution.

Usage

do_likelihood_profile(
  data,
  parameters,
  mapping,
  random = NULL,
  what,
  idx = NULL,
  min_val,
  max_val,
  inc = 0.05,
  do_par = FALSE,
  n_cores = NULL
)

Arguments

data

Data list from the fitted model.

parameters

Parameter list from the fitted model.

mapping

Mapping list from the fitted model.

random

Character vector of random effects to estimate. Default NULL.

what

Character string. Name of the parameter to profile.

idx

Vector pointing to the specific elements to fix when parameters[[what]] is an array. NULL for scalar parameters.

min_val

Numeric. Minimum value of the profile range.

max_val

Numeric. Maximum value of the profile range.

inc

Numeric. Increment between profile values. Default 0.05.

do_par

Logical. Whether to use parallel processing. Default FALSE.

n_cores

Integer. Number of parallel workers. If NULL (default), parallel::detectCores() - 1 is used.

Value

A named list containing one dataframe per likelihood component, each with a prof_val column indicating the profiled parameter value, plus agg_nLL which aggregates all components across their respective dimensions. Components include:

Scalar penalties and priors

jnLL_df, rec_nLL_df, M_nLL_df, sel_nLL_df, rec_prop_nLL_df, Movement_nLL_df, h_nLL_df, TagRep_nLL_df, Fmort_nLL_df, fish_q_nLL_df, srv_q_nLL_df.

Pooled data likelihoods

Catch_nLL_df [Region × Year × Seas × Fleet], FishIdx_nLL_df and SrvIdx_nLL_df [Region × Year × Seas × Fleet], FishAge_nLL_df, FishLen_nLL_df, SrvAge_nLL_df, SrvLen_nLL_df [Region × Year × Seas × Sex × Fleet], conv_fish_tag_nLL_df [Recap_Year × Recap_Seas × Tag_Cohort × Region × Fleet].

Population-specific data likelihoods

Catch_pop_nLL_df, FishIdx_pop_nLL_df, SrvIdx_pop_nLL_df [Pop × Region × Year × Seas × Fleet], FishAge_pop_nLL_df, FishLen_pop_nLL_df, SrvAge_pop_nLL_df, SrvLen_pop_nLL_df [Pop × Region × Year × Seas × Sex × Fleet].

See also

Other Model Diagnostics: do_jitter(), do_retrospective(), do_runs_test(), get_catch_fits_plot(), get_comp_prop(), get_idx_fits(), get_idx_fits_plot(), get_model_rep_from_mcmc(), get_nLL_plot(), get_osa(), get_retrospective_plot(), get_retrospective_relative_difference(), plot_resids()