Changes in version 0.3.2 (2026-07-30)                  

  - DESCRIPTION: spelled out all acronyms and added method references
    with DOIs (Griffing 1956; Eberhart & Russell 1966), per CRAN review.
  - inst/examples/run_all.R now writes figures to tempdir() instead of
    the working directory, in line with CRAN policy.

                        Changes in version 0.3.1                        

  - Wrapped the \usage line in bk_diversity.Rd to satisfy the Rd
    line-width check (CRAN incoming pre-test); no user-visible change.
  - Added inst/WORDLIST documenting the plant-breeding terms flagged by
    the spell checker (all correct).

                        Changes in version 0.3.0                        

  - New bk_diallel() — Griffing (1956) diallel analysis, Method 2
    (parents + one set of F1s, no reciprocals), Model I (fixed):
    combining-ability ANOVA (GCA, SCA), parental GCA effects, SCA
    matrix, Baker's predictability ratio and variance components.
    Standard errors are computed exactly by propagating the per-entry
    error variance through the linear estimators (no tabulated
    constants).
  - bk_plot() gains a bk_diallel method: GCA effect bars (default) and
    an SCA heatmap (type = "sca").
  - New bundled dataset bk_data("diallel") — 6-parent half diallel, 3
    reps.

                        Changes in version 0.2.0                        

  - New bk_lxt() — Line x Tester combining-ability analysis:
    combining-ability ANOVA (crosses partitioned into lines, testers and
    line x tester), GCA effects for lines and testers, SCA effects per
    cross, proportional contributions, and GCA/SCA variance components
    with additive/dominance variances, average degree of dominance and
    predictability ratio.
  - bk_plot() gains a bk_lxt method: GCA effect bars (default) and an
    SCA heatmap (type = "sca").
  - New bundled dataset bk_data("lxt") — 5 lines x 3 testers, 3
    replications.

                        Changes in version 0.1.0                        

First release.

  - Experimental designs: bk_rbd(), bk_frbd(), bk_augmented() (Augmented
    Alpha-Lattice and Augmented RCBD).
  - Biometrical genetics: bk_variability(), bk_correlation(), bk_path(),
    bk_diversity() (Mahalanobis D² with Tocher and Ward clustering),
    bk_stability() (Eberhart-Russell + AMMI).
  - A single bk_plot() verb returns a publication-ready ggplot2 figure
    for every result, using the bespoke theme_bk() and bk_palette()
    colour system.
  - Four bundled example datasets via bk_data().
  - Full demonstration script at inst/examples/run_all.R.