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

Orchestrates data preparation, validation, and passes it to the C++ MCMC engine.

Usage

pooling_surv_bridge(
  processed,
  pooling,
  priors,
  iter,
  warmup,
  thin,
  chains,
  parallel_chains,
  group_col,
  original_data,
  seed = NULL,
  verbose = TRUE
)

Arguments

processed: A list produced by `hardhat::mold()`.
pooling: Pooling mode; see pooling_surv().
priors: Optional named list of prior hyperparameters; see pooling_surv().
iter: Total number of MCMC iterations.
warmup: Number of warmup iterations.
thin: Thinning interval for the post-warmup draws.
chains: Number of chains to run.
parallel_chains: Number of chains to run in parallel at the R level.
group_col: Name of the original group column.
original_data: The original data frame (before hardhat processing).
seed: Optional seed used to deterministically derive one seed per chain.

Value

An `pooling_surv` object.

Details

The group variable (specified by group_col) is identified from the original data. Additional variables are treated as covariates in the linear predictor.