Changes in version 0.2.0 (2026-08-21)                  

  - First CRAN submission. The package was previously available on
    GitHub under version 0.1.0.
  - The bundled identity and identity_w datasets now use item names for
    the marginal-rank columns: party, religion, gender, race (previously
    app_identity_1--app_identity_4) and household, neighborhood, city,
    state (previously anc_identity_1--anc_identity_4). Examples and
    vignettes now pass these columns explicitly, e.g. main_q =
    c("party", "religion", "gender", "race").
  - New exported function rank_wider() for converting long-format
    ranking data to wide format (one column per item or a single pasted
    ranking string).
  - imprr_direct(): anc_correct is now optional. Users can instead
    supply p_random directly, or rely on anchor-based estimation of the
    non-random response rate.
  - New exported convenience wrapper add_ipw_weights() for returning the
    original data augmented with respondent-level IPW weights, with an
    option to also keep ranking summaries.
  - imprr_direct_rcpp(): correctly delegates to imprr_direct() when
    method = "fixed", forwarding all population and assumption inputs.
  - rpluce(): when all remaining Plackett-Luce weights become zero after
    earlier draws, the remaining items are now sampled uniformly at
    random rather than being ordered by input position.
  - rank_longer(): stricter validation on the reference argument and
    clearer handling of single- vs multi-column input.
  - Stronger input validation across the package: weights must be
    finite, non-negative, and sum to a positive number; J must be
    finite; permutation labels are parsed consistently across compact,
    delimited, and fixed-width formats (including J > 9).
  - Permutation-label infrastructure rewritten to support rankings of
    arbitrary size.
  - Documentation: switched to \href{}{} for external URLs; expanded
    examples and \value{} sections.

                        Changes in version 0.1.0                        

  - Initial GitHub release (not submitted to CRAN).
  - Implements design-based bias correction methods for ranking survey
    questions, based on Atsusaka and Kim (2025) doi:10.1017/pan.2024.33.
  - Core functions for bias correction: imprr_direct(),
    imprr_direct_rcpp(), and imprr_weights().
  - Rcpp backend for bootstrap-based estimation.
  - Visualization functions: plot_avg_ranking() and plot_dist_ranking().
  - Utility functions for ranking data manipulation: rank_longer(),
    item_to_rank(), recover_recorded_responses(), and permn_augment().
  - Statistical testing with uniformity_test().
  - Simulation support with rpluce() for Plackett-Luce sampling.
  - Includes example dataset from an identity ranking survey.