Package index • mbmm

Fit the model

Top-level fitting functions

mbmm(): Fit a bank-based MBMM analysis

mbmm_fit_gate(): Fit the MBMM gate model

mbmm_abc_fit(): Fit an ABC rejection-sampling posterior for one subject

ABC reference banks

Build and pool Approximate Bayesian Computation banks

mbmm_abc_bank(): Fit ABC posteriors for multiple subjects or donors

mbmm_pool_bank(): Pool per-donor ABC particles into a mechanistic reference bank

mbmm_predict_bank(): Predict mechanistic bank trajectories at required observation times

mbmm_join_targets(): Join target-specific particle banks into complete multitarget bundles

Gate model

Covariate-linked latent-class gate

mbmm_gate_threshold(): Fitted MBMM gate threshold for a continuous covariate

mbmm_bootstrap_gate_threshold(): Bootstrap an MBMM gate threshold

mbmm_backtransform_threshold(): Back-transform an MBMM gate threshold

mbmm_predict_gate(): Predict fitted MBMM gate probabilities

summary(<mbmm_gate>): Summarize an mbmm_gate object

print(<mbmm_gate>): Print an mbmm_gate object

plot(<mbmm_gate>): Plot a fitted MBMM gate curve against one continuous covariate

Scoring and thresholds

mbmm_score_subjects(): Score every subject against class-specific reference banks

mbmm_class_loglik(): Reference-bank class-conditional log-likelihood for one subject

mbmm_noise_floor_loglik(): Analytic non-establishment class likelihood for COVID5001-style analyses

summary(<mbmm_threshold_summary>): Summarize an MBMM threshold summary

print(<mbmm_threshold_summary>): Print an MBMM threshold summary

Simulation and demo data

Simulate trajectories and example datasets used in the vignettes

mbmm_simulate_demo_antibody(): Simulate a fully synthetic baseline antibody measurement

mbmm_simulate_abortive_pattern(): Simulate one transient or abortive detection pattern

mbmm_simulate_cop_demo(): Simulate a synthetic correlate-of-protection cohort

mbmm_simulate_manuscript_demo(): Simulate a reduced manuscript-style MBMM dataset

mbmm_example_eclipse_simulate(): Example mechanistic trajectory model: eclipse-phase viral kinetics

mbmm_example_eclipse_prior(): Example ABC prior sampler for the eclipse-phase model

mbmm_demo_visit_schedules(): Public visit schedules for the reduced MBMM simulation

mbmm_demo_scenario_grid(): Create the default reduced manuscript-style scenario grid

mbmm_run_simulation_grid(): Run a manuscript-style simulation grid

mbmm_productive_infection(): Fit a productive-infection MBMM analysis

Model fit objects

summary(<mbmm_fit>): Summarize an mbmm_fit object

print(<mbmm_fit>): Print an mbmm_fit object

plot(<mbmm_fit>): Plot the bank log-likelihood-ratio diagnostic for an MBMM fit

Numerical utilities

mbmm_rk4_solve(): Fixed-step 4th-order Runge-Kutta ODE integrator (base R, no dependencies)

mbmm_logsumexp(): Numerically stable log-sum-exp

mbmm_logmeanexp(): Numerically stable log-mean-exp

mbmm_logit(): Logit

mbmm_inv_logit(): Inverse logit

mbmm_safe_log10(): Safe log10 with a positive floor

mbmm_dnorm_censored(): Gaussian log-density with optional left censoring at an LOD

mbmm_default_distance(): Default ABC discrepancy: censoring-aware weighted RMSE on the log10 scale