Changes in version 0.1.1                        

CRAN resubmission — corrections requested by reviewers

  - DESCRIPTION — Description field now cites the three core methods
    using the authors (year) <doi:...> format required by CRAN: Efron &
    Tibshirani (1993, ISBN:9780412042317), Meinshausen & Bühlmann (2010)
    <doi:10.1111/j.1467-9868.2010.00740.x>, and Peng (2011)
    <doi:10.1126/science.1213847>.

  - Examples — \dontrun{} replaced with \donttest{} in
    plot_stability_gg.Rd and plot_cv_stability_gg.Rd; optional-package
    examples are now guarded with a requireNamespace() check inside
    \donttest{}.

  - par() save/restore — all calls to par(mfrow = ...) in
    demo/reprostat.R and vignettes/ReproStat-intro.Rmd now follow the
    oldpar <- par(...); on.exit(par(oldpar)) pattern so that global
    graphics settings are restored after each code block.

                        Changes in version 0.1.0                        

Initial release

  - run_diagnostics(): main entry point supporting "lm", "glm", "rlm"
    (via MASS), and "glmnet" (via glmnet) backends; three perturbation
    methods ("bootstrap", "subsample", "noise"). New argument
    perturb_response (default FALSE) controls whether the response
    column is perturbed under the noise method.
  - perturb_data(): standalone data perturbation with bootstrap,
    subsampling, and Gaussian noise injection. New argument response_col
    allows the response column to be excluded from noise perturbation.
  - coef_stability(): variance of coefficient estimates across
    perturbation iterations.
  - pvalue_stability(): proportion of iterations in which each predictor
    is significant; intercept excluded from output.
  - selection_stability(): sign consistency of estimated coefficients
    for "lm" / "glm" / "rlm" backends; non-zero selection frequency for
    the "glmnet" backend. Intercept excluded. This is a genuinely
    distinct measure from pvalue_stability().
  - prediction_stability(): pointwise prediction variance across
    perturbation iterations.
  - reproducibility_index(): composite 0--100 Reproducibility Index.
      - Coefficient component (c_beta) now uses a global scale reference
        (median(|base_coef|)) instead of a hard-coded epsilon,
        preventing the score from collapsing for near-zero coefficients.
      - c_p (p-value stability) and c_sel (selection stability) are now
        genuinely distinct components; they previously computed the same
        quantity.
      - For backend = "glmnet", the selection component (c_sel) is now
        the mean non-zero selection frequency and is always available
        (previously it was NA). The RI for glmnet is therefore based on
        three components instead of two.
  - ri_confidence_interval(): bootstrap confidence interval for the RI.
    The seed argument now defaults to NULL, leaving the caller's global
    RNG state undisturbed. Pass an integer to fix the seed explicitly.
  - cv_ranking_stability(): repeated K-fold CV ranking stability for
    model comparison across the same four backends.
  - plot_stability(), plot_cv_stability(): base-graphics visualisations.
  - plot_stability_gg(), plot_cv_stability_gg(): optional ggplot2-based
    equivalents (require ggplot2).