Package index • tinyAM

Model overview and example data

make_tam_data(): Construct tinyAM input data from tables
as_tam_data() print(<tam_data>): Organize tinyAM input data
check_tam_data(): Check tinyAM input data
cut_int() cut_ages() cut_years(): Cut integer sequences into labeled blocks (ages or years)
prepare_tam(): Build a self-contained data list for TAM
make_par(): Initialize parameter list for TAM

bh() ricker(): Recruitment formulas and stock-recruit relationships
logistic() mono(): Rising catchability and mean fishing-mortality curves
double_logistic(): Double-logistic selectivity curves
for_fleet() for_survey(): Apply a formula within one fleet or survey
smooth_formulas: Penalized smooth F and catchability relationships
power(): Abundance-dependent catchability
iid() rw() ar1(): Random effects in model formulas

fit_tam(): Fit a Tiny Assessment Model (TAM)
update(<tam_fit>): Update a fitted TAM model
check_tam() print(<tam_check>) print(<tam_checks>): Check numerical convergence and model diagnostics
logLik(<tam_fit>) AIC(<tam_fit>) cAIC(): Compare fitted models using information criteria
print(<tam_fit>) summary(<tam_fit>) print(<summary_tam_fit>): Print and summarize a TAM fit
fit_retro() fit_hindcast() print(<tam_retro>): Retrospective fits and observation hindcasts
compute_hindcast_rmse(): Compute hindcast RMSE (observed vs projected)
compute_hindcast_mase(): Persistence-relative hindcast forecast error
compute_mohns_rho(): Compute Mohn's rho for retrospective analyses
sim_tam(): Simulate from a fitted TAM

vis_tam(): Make a flexdashboard for visualizing model fits
plot_model(): View the structure of fitted assessment models
plot_heatmap() plot_par() plot_bubbles() plot_resid() plot_trend() plot_obs_pred() add_plot_buttons(): Plot utilities for tidy_tam() outputs
plot_age_year(): Switch between annual trends and age profiles
plot_matrix(): Explore age-year patterns
plot_process_deviations() plot_process_residuals(): Explore fitted process deviations and joint-sample residuals
tam_cols() tam_pal(): TAM color palette helpers

tidy_tam(): Stack TAM outputs across models (retro folds, scenarios, etc.)
tidy_obs_pred(): Tidy observed, predicted, and residual diagnostics
residuals(<tam_fit>): Extract observation residuals
add_osa_residuals(): Calculate and retain one-step-ahead residuals
tidy_pop(): Collect population trends and age-specific estimates
get_ssb() get_recruitment() get_fbar() get_mbar() get_f() get_m(): Extract common population estimates
tidy_par(): Tidy parameter estimates (fixed & random) with CIs and back-transforms
tidy_recruitment(): Tidy recruitment relationships and residuals
tidy_sdrep(): Population time series with confidence intervals
tidy_rep(): Tidy reported trends
tidy_array(): Tidy a (named) matrix/array into long format
stack_list(): Stack a list of tables with an identifier column
stack_nested(): Stack identically named subtables from a nested list
trans_est(): Transform and rescale estimate columns

nll_fun(): Evaluate or simulate the tinyAM model
dprocess_rw() rprocess_rw(): Temporal random-walk process: density and simulation
dprocess_ar1() rprocess_ar1(): Separable AR1 process error: density and simulation
dprocess_cor_rw() rprocess_cor_rw(): Random walk with age-correlated increments: density and simulation