Changes in version 0.1.0 (2026-06-22)                  

First public release. Initial feature set:

  - sampling(): fits the imuGAP Bayesian hierarchical coverage model via
    rstan::sampling() and returns an imugap_fit object wrapping the
    underlying stanfit together with model settings and dataset
    metadata.
  - predict.imugap_fit(): posterior-predicts coverage probabilities for
    a user-supplied target population grid using rstan::gqs().
  - extract_imugap(): convenience wrapper around rstan::extract() for
    pulling out common imuGAP parameters (defaults to the state-level
    B-spline coefficients beta_bs).
  - canonicalize_locations(), canonicalize_observations(),
    canonicalize_populations(): validate and convert user-supplied data
    into the canonical forms required by the sampler.
  - imugap_options(): configures model-side settings (B-spline degrees
    of freedom, dose schedule, model object).
  - stan_options(): configures Stan sampler settings (iter, chains,
    seed, etc.) with input validation.
  - Bundled Stan models:
      - impute_school_coverage_process_v6 (adds county- and school-level
        random effects; current default).
  - Bundled example datasets for end-to-end examples and tests:
    locations_sim, observations_sim, populations_sim, latent_params_sim,
    predict_sim, target_sim, and the reference fit_sim stanfit fixture.
  - pkgdown documentation site published at
    https://accidda.github.io/imuGAP/.