Changes in version 0.2.0 (2026-07-19)                  

Robustness (pre-release stress campaign; see validation/robustness/REPORT.md)

  - Univariate data now default to single linkage: the components of 1-D
    clusters form a chain that Ward's linkage cuts unreliably.
  - Unconverged Hartigan-Wong K-means solutions (Quick-TRANSfer cap at
    large n) are polished with Lloyd iterations so that the stored
    components are consistent with the stored centers and predict()
    reproduces them.
  - Diverging classification EM for the heteroscedastic variants (an
    instability inherent in their implied mixing proportions) now
    returns the last stable iteration with a warning instead of failing
    with an internal error; converged CEM fits return exactly the
    parameters that generated the labels, restoring the predict()
    round-trip.
  - G = "auto" is now computed from the single-linkage merge sequence of
    the overlap matrix regardless of the fitting linkage (the previous
    Ward-height gaps were unreliable); its limits (range 2:(K-1),
    spurious suggestions on structureless data) are documented.
  - Fixed: variant = "HeEC" crashed on univariate data; plot(fit, what =
    "tree") failed for K = 2; Inf values slipped past validation into
    cryptic downstream errors (MergeKmeans, predict, chooseK);
    overlap_map() crashed on missing values; predict() silently
    propagated NA.
  - kmeans++ seeding subsamples very large datasets (n > 1e5), removing
    the dominant cost of the n = 1e6, large-K regime.
  - New documentation: linkage guidance (Ward vs unequal cluster sizes
    and 1-D chains), contamination tolerance, heavy-tailed vs skewed
    clusters.

New features

  - init = "kmeans++" is the new default initialization of the K-means
    restarts (Arthur & Vassilvitskii, 2007), stabilizing the large-K
    component solutions on which the merging is built; init = "random"
    restores the previous behavior.
  - start argument: MergeKmeans() can now merge a partition computed by
    any external engine (a kmeans object, a ClusterR-style list, or a
    bare label vector), skipping its own K-means step entirely. This
    removes the single-threaded stats::kmeans ceiling for very large
    datasets.
  - G = "auto" cuts the merge tree at the largest gap in merge heights
    (also available in recut()); when no G/omega.star is supplied the
    fit-time message now reports the suggested G.
  - K = NULL (new default) selects the number of components
    automatically via chooseK().
  - chooseK() now reports and marks a recommended K (one grid step
    beyond the detected elbow) and gained a cores argument.
  - cores argument forks the K-means restarts via the parallel package
    (POSIX systems).
  - broom tidiers: tidy(), glance(), and augment() methods are
    registered when broom is loaded.

User-facing changes

  - Variant names are matched case-insensitively and accept
    plain-language aliases ("spherical", "elliptical",
    "spherical-unequal", "elliptical-unequal").
  - omega.star with Ward's linkage is now an error (it previously warned
    and returned a degenerate unmerged partition).
  - A warning is emitted when components contain single observations (K
    too large relative to n).
  - Documentation: scaling guidance, a "when to use what" discussion
    (including the recommendation to prefer model-based clustering for
    genuinely overlapping Gaussian ellipsoids), and a recipe for merging
    mini-batch K-means solutions of massive datasets.

                        Changes in version 0.1.0                        

  - Initial version: DEMP-K merging of K-means solutions (Melnykov &
    Michael, 2020) with the four K-means variants (HoSC, HoEC, HeSC,
    HeEC), exact pairwise-overlap computations,
    single/Ward/average/complete linkages, the overlap map display,
    recut(), chooseK(), pairwise_overlap(), and
    print/summary/plot/predict methods.
  - All overlap computations validated against MixSim::overlap() and by
    independent Monte Carlo simulation; the paper's illustrative
    examples and pen-digits application reproduced.