Package index

Fitting

Fit an EXNEX survival model to right-censored data.

exnex_surv()

Fit Bayesian EXNEX Survival Models

Inference and model selection

Posterior summaries, survival curves, model comparison and simulation.

survival_curves()

Survival curves from an exnex_surv fit

plot(<survival_exnex>)

Plot survival curves from an exnex_surv fit

median_survival()

Posterior median survival time

rmst()

Restricted mean survival time (RMST) from an exnex_surv fit

compute_waic()

Pointwise log-likelihood and WAIC from an exnex_surv fit

compare_waic()

Compare multiple exnex_surv fits by WAIC

probability_superiority()

Posterior probability that one group beats another

simulate_data()

Simulate basket-trial log-normal survival data

Methods for fitted objects

Summarise, print, and plot fitted exnex_surv objects.

summary(<exnex_surv>)

Summarize posterior draws from an exnex_surv fit

print(<exnex_surv>)

Print an exnex_surv fit

plot(<exnex_surv>)

Plot parameter traces from an exnex_surv fit

Internal functions

These functions are internal and not exported; use with caution.

cpp_exnex_gibbs()

Main Gibbs Sampler for EXNEX Survival Models

exnex_surv_bridge()

Bridge connecting hardhat processed data to the C++ Gibbs Sampler

new_exnex_surv()

Constructor for exnex_surv Objects

.extract_event_vector()

Extract event vector from outcomes

.extract_time_vector()

Extract time vector from outcomes

.make_chain_seeds()

Derive one deterministic seed per chain (restores the global RNG state)

.run_chains_parallel_exnex()

Run multiple chains in parallel via PSOCK workers

.run_single_chain_exnex()

Run a single chain by calling the C++ kernel once