Package index • opal

Assessment objects

Create, fit, sample, inspect, and save one portable assessment.

opal_obj(): Create a portable Opal assessment object
opal_build() opal_rtmb(): Build or access an Opal runtime objective
opal_fit(): Fit an Opal assessment
opal_update(): Update an Opal model configuration
opal_attach_fit(): Attach an externally optimised Opal fit
opal_mcmc(): Run MCMC for an Opal object
opal_attach_mcmc(): Attach posterior draws to an Opal object
opal_check(): Check fitted or sampled Opal results
opal_report(): Report a configured or fitted Opal model
opal_save() opal_read(): Save and read staged Opal objects
summary(<opal_obj>) print(<summary.opal_obj>) print(<opal_obj>): Summarise a staged Opal assessment
validate_opal_obj(): Validate a staged Opal object
opal_from_fit(): Convert a legacy Opal fit to the staged object workflow
opal_as_tmbfit(): Convert normalized opal posterior draws to a tmbfit

Assessment diagnostics and summaries

opal_diagnose(): Diagnose biological feasibility of an Opal model
opal_osa(): Calculate one-step-ahead observation residuals
plot_osa_sdnr(): Compare OSA residual dispersion across datasets
plot_osa_residuals(): Plot stored OSA residuals
plot_composition(): Plot observed and fitted compositions
plot_prior_posterior(): Compare parameter priors and posterior distributions
opal_posterior(): Summarise posterior parameters and derived model quantities
opal_derived(): Retrieve a stored assessment analysis
opal_example_inputs(): Simulated inputs for the assessment-tools tutorial

Sensitivities and reference points

opal_profile(): Profile an assessment parameter
plot_opal_profile(): Plot an objective profile
opal_grid(): Fit a reproducible grid of assessment scenarios
opal_grid_mcmc(): Sample accepted members of an assessment grid
opal_grid_draws(): Select balanced posterior draws from a model grid
opal_msy(): Calculate deterministic equilibrium reference points

Projections

Specify future assumptions and retain projections with their source assessment.

opal_project(): Project an Opal object and retain the result
project_dynamics(): Project dynamics
project_rec_devs(): Project recruitment deviates
project_selectivity(): Project selectivity

Plots

Pass an assessment object directly to the model plots.

plot_biomass_spawning(): Plot spawning biomass
plot_catch(): Plot catch
plot_cpue(): Plot CPUE
plot_hrate(): Plot harvest rate
plot_initial_numbers(): Plot initial numbers
plot_recruitment(): Plot recruitment

Model inputs and diagnostics

Prepare data, configure parameters, and inspect the underlying RTMB model.

opaka_quickstart_inputs(): Opakapaka quickstart model inputs
get_data(): Get bundled model data
get_parameters(): Get bundled initial parameter values
get_map(): Get default parameter mapping
get_bounds(): Get default parameter bounds
get_priors(): Get priors
prep_lf_data(): Prepare length composition data for model input
prep_wf_data(): Prepare weight composition data for model input
check_bounds(): Check if parameters are up against the bounds
check_estimability(): Check for identifiability of fixed effects
get_cor_pairs(): Return strongly-correlated parameter pairs
get_par_table(): Summarise model parameters in a table
extract_fixed(): Extract fixed effects

Model components

Lower-level functions used by the assessment model and advanced workflows. The natural-mortality plot takes a data list and an RTMB runtime.

plot_natural_mortality(): Plot natural mortality
cmb(): Helper to make closure
convert_rtmb_selex_to_ss3(): Convert RTMB real-line selectivity parameters back to SS3 natural scale
convert_ss3_selex_to_rtmb(): Convert SS3 selectivity parameters to RTMB real-line parameterization
do_dynamics(): Population dynamics
double_richards_natural(): Convert double Richards parameters to natural scale
evaluate_priors(): Evaluate priors
get_bias_adj_vector(): Calculate Recruitment Bias Adjustment Ramp
get_cpue_like(): CPUE index likelihood (multi-index)
get_growth(): Compute mean length-at-age using the Schnute parameterization of VB growth
get_harvest_rate(): Harvest rate calculation
get_initial_numbers(): Initial numbers and Beverton-Holt parameters
get_length_like(): Length Composition Likelihood
get_maturity_at_age(): Convert maturity-at-length to maturity-at-age
get_pla(): Probability of length at age matrix (age-length key)
get_recruitment(): Calculate recruitment
get_recruitment_prior(): Recruitment prior
get_sd_at_age(): Compute SD of length-at-age from CV1 and CV2
get_selectivity(): Compute selectivity-at-age from length-based selectivity curves
get_unfished_init(): Compute unfished equilibrium quantities from natural mortality only
get_weight_at_length(): Compute weight at each length bin midpoint
get_weight_like(): Weight Composition Likelihood
opal_globals(): The opal globals
opal_model(): The opal model
posfun(): Positive Constraint Penalty Function
rebin_counts(): Linear area rebinning of frequency data
rebin_matrix(): Compute rebinning weight matrix
resolve_bio_vector(): Resolve a biology vector to age-basis
sel_double_normal(): Double-normal selectivity as a function of length (SS3 pattern 24, full form)
sel_double_richards(): Double Richards selectivity as a function of length
sel_length(): Selectivity-at-length for a single fishery, dispatched on type code
sel_logistic(): Logistic selectivity as a function of length

Bundled data

Example inputs and numerical baseline datasets.

opaka_data: 'Opakapaka Stock Assessment Data
opaka_lf: 'Opakapaka Length Frequency Data
opaka_parameters: 'Opakapaka Stock Assessment Parameters
opaka_truth: Opakapaka SS3 OM/EM truth and EM output (extracted)
opal_baseline: opal model regression baseline
opal_baseline_data: Opal Baseline Data
opal_baseline_map: Opal Baseline Map
opal_baseline_parameters: Opal Baseline Parameters
wcpo_bet_data: West Central Pacific Ocean Bigeye Tuna (WCPO BET) Assessment Data
wcpo_bet_lf: West Central Pacific Ocean Bigeye Tuna (WCPO BET) Length Frequency Data
wcpo_bet_parameters: West Central Pacific Ocean Bigeye Tuna (WCPO BET) Assessment Parameters
wcpo_bet_wf: West Central Pacific Ocean Bigeye Tuna (WCPO BET) Weight Frequency Data

Legacy fit compatibility

Compatibility helpers for older opal_fit files; use opal_obj for new assessments.

opal_fit_compatibility(): Check compatibility of a saved opal fit
save_opal_fit() read_opal_fit(): Save and read portable opal fits
opal_fit_object(): Access the runtime objective for an opal fit
opal_fit_report(): Recreate the fitted model report
rebuild_opal_object(): Rebuild the RTMB objective for a portable opal fit
update_opal_fit(): Update portable results attached to an opal fit
validate_opal_fit(): Validate a portable opal fit