Fits an approved binary model specification using full MCMC sampling through
the fixed brms and rstan route.
Usage
fit_binary_model(
specification,
chains = 4L,
iter = 2000L,
warmup = 1000L,
cores = .gp3b_default_cores(chains),
seed = 1L,
adapt_delta = 0.95,
max_treedepth = 12L,
refresh = 0L
)Arguments
- specification
A
gp3bayes_binary_model_specification.- chains
Number of MCMC chains.
- iter
Total iterations per chain, including warmup.
- warmup
Warmup iterations per chain.
- cores
Number of processor cores. It cannot exceed
chains.- seed
Non-negative integer random-number seed.
- adapt_delta
Target acceptance probability for the No-U-Turn sampler.
- max_treedepth
Maximum tree depth for the No-U-Turn sampler.
- refresh
Console progress refresh interval. Use zero to suppress iteration progress output.
Value
A gp3bayes_binary_fit containing the fitted backend object,
original specification, restricted translation, and recorded sampling
settings.
Details
The function fixes the likelihood to Bernoulli, the link to logit, the
interface to brms, the sampling backend to rstan, and the algorithm to
full MCMC sampling. It does not expose arbitrary backend arguments.
A returned fit is not evidence of convergence, posterior adequacy, causal identification, or substantive validity. Those assessments require separate diagnostic and reporting gates.