Changes in version 0.1.0 (2026-06-22)                  

  - Initial CRAN release.

  - Provides seven fast k-means clustering algorithms behind a single,
    uniform interface, wrapping high-performance C++ implementations via
    'Rcpp' and 'RcppEigen':
    
      - geo_kmeans() — Geometric-k-means, the bound-free method of
        Sharma et al. (2026) doi:10.1007/s10994-025-06891-1.
      - ball_kmeans() — Ball k-means++.
      - lloyd_kmeans(), elkan_kmeans(), hamerly_kmeans(),
        annulus_kmeans(), and exponion_kmeans().
      - kmeans_dc() — dispatcher to select any of the above by name.

  - centers accepts either the number of clusters or a matrix of initial
    centroids (mirroring stats::kmeans()); initialisation can be
    "random" or "sequential".

  - Returns a geokmeans object with the final centroids, per-point
    cluster assignments, iteration count, and number of distance
    computations, along with a print() method.

  - Random initialisation uses R's random number generator and is
    reproducible via set.seed() or the optional seed argument (default
    NULL).

  - Safeguards for degenerate input: an informative error when more
    clusters are requested than there are distinct observations, and
    optional removal of empty clusters via drop_empty.

  - Ships two example datasets in inst/extdata (Breastcancer.csv and
    CreditRisk.csv) and a "Getting started with geokmeans" vignette.