ReproStat 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.

ReproStat 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).