Changes in version 1.0.1 (2026-08-09)                  

CRAN resubmission after reviewer feedback. No statistical results
change.

  - The Description field now cites the accompanying paper: Harshvardhan
    and Ranjan (2026) doi:10.48550/arXiv.2607.22285.
  - The ggcor_heatmap() / ggcor_method_heatmap() example is no longer
    wrapped in \dontrun{}; it uses only bundled data and runs during
    checks.
  - The internal seed helper no longer touches the global environment
    directly; it delegates to withr::with_seed() (withr added to
    Imports). Seeded results are unchanged, and a seeded call still
    restores the caller's .Random.seed.
  - graphics and utils are now declared in Imports (both were already
    imported in NAMESPACE).
  - inst/CITATION, the README, and the documentation now cite the
    published arXiv preprint (arXiv:2607.22285) instead of "work in
    progress".

                        Changes in version 1.0.0                        

First public release.

  - smart_cor() detects the types of two variables and selects an
    appropriate correlation method (Pearson, Spearman, Kendall's tau-b,
    polychoric, polyserial, tetrachoric, point-biserial, rank-biserial,
    Goodman-Kruskal gamma, or phi), with analytic inference on the
    Fisher-z scale and optional bootstrap.
  - smart_cormat() and smart_cor_df() extend automatic selection to full
    mixed-type data frames and correlation matrices.
  - compare_methods() reports all applicable estimators for a pair side
    by side.
  - test_bivariate_normality() implements the likelihood-ratio
    chi-square test for bivariate normality (Joreskog 2005); smart_cor()
    runs it automatically before reporting polychoric/polyserial
    estimates and falls back to Kendall's tau-b when it rejects.
  - detect_type() and available_methods() expose the type-detection and
    method-lookup machinery.
  - Heatmap visualizations: ggcor_heatmap(), ggcor_method_heatmap(), and
    plot_cor_heatmap().
  - tidy() method for pipeline-friendly output.