Skip to contents

Changelog

Source: NEWS.md

imuGAP 0.2.0

CRAN release: 2026-09-02

Major Features

  • Arbitrary Hierarchy Layer Depth:
    • sampling(), canonicalize_locations(), and underlying Stan models now support user-defined hierarchical location structures of arbitrary depth (e.g. 1-layer statewide, 2-layer state-county, 3-layer state-county-school, or deeper regional partitions).
    • Added assemble_layer_data() helper to construct and validate hierarchical metadata, bounds, and parent mappings.
    • Added dedicated single-layer model impute_school_coverage_process_v6_single_layer with automatic dispatch when single-layer inputs are supplied.
    • Added a new vignette (user_specified_layers) demonstrating 1-layer, 2-layer, and 3-layer model estimation and prediction workflows.
  • Backend Abstraction via flexstanr:
    • Integrated flexstanr (>= 0.2.0) to provide uniform backend abstraction across rstan and cmdstanr MCMC engines.
    • Re-exported flexstanr::stan_options() for seamless sampler configuration.
  • Modular Stan Architecture:
    • Refactored top-level Stan models into concise assembly skeletons utilizing modular #include directives (functions/, data/, transformed_data/, parameters/, model/).
    • Pruned legacy/vestigial Stan scripts to streamline code base maintenance.
  • Data Pipeline & Target Generation:
    • Split target generation into fit-free constructor create_target() and validation function canonicalize_target().
    • Added bundled example fitted datasets for single-layer and 2-layer models (fit_sim_1layer, fit_sim_2layer, predict_sim_1layer, predict_sim_2layer, target_sim_1layer, target_sim_2layer).

Enhancements & Bug Fixes

  • Location Hierarchy Invariant: Enforced structural validation ensuring location nodes have either 0 offspring (leaf) or ≥2\ge 2 offspring (preventing single-child degenerate chains).
  • Error Handling & Assertions: Standardized assertion messages across all functions using module-level ERR_* format string constants and helper assertion functions stop_fmt_if() and warn_fmt_if().
  • Validation: Added validation against NA weights in population and target specifications.
  • Documentation Examples & Check Times: Applied combined @examplesIf interactive() and \donttest{} idiom to computationally heavy examples, enabling fast pkgdown builds (~35 seconds) while remaining CRAN --as-cran compliant.
  • Vignette Dark Mode Compatibility: Enforced solid white backgrounds and high-contrast styling across all vignette plots for clean rendering in light/dark modes.

imuGAP 0.1.0

CRAN release: 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/.