Changes in version 0.2.1 (2026-06-08)                  

Breaking changes

  - Removed predict.bean_ellipsoid(). The canonical implementation now
    lives in the companion package nicheR.

New features

  - bean_ellipsoid objects returned by fit_ellipsoid() now carry a
    second S3 class, "nicheR_ellipsoid", and include the fields nicheR's
    predict.nicheR_ellipsoid() method expects: dimensions, cov_matrix,
    Sigma_inv, cl, var_names, and chi2_cutoff. As a result, once nicheR
    is loaded its predict() method dispatches directly on objects
    produced by bean::fit_ellipsoid() without any explicit conversion.
  - The existing centroid, covariance_matrix, points_in_ellipse, etc.
    fields are preserved for backward compatibility.
  - fit_ellipsoid() now pre-computes the inverse covariance matrix
    (Sigma_inv) using solve(), with a Moore-Penrose pseudo-inverse
    fallback (via SVD) and a warning if the covariance matrix is
    singular.

Documentation

  - Vignette "3. Niche modeling" no longer ships a predict / suitability
    section; it shows the nicheR integration instead, with a plain-terra
    fallback for users who do not yet have nicheR installed.
  - README, vignette and fit_ellipsoid() references now direct users who
    want to project a bean_ellipsoid into geographic space to install
    nicheR and cite Castaneda-Guzman et al. (2026), nicheR:
    Ellipsoid-Based Virtual Niches and Visualization.

                 Changes in version 0.2.0 (2026-05-30)                  

Major changes

  - find_env_resolution() no longer uses a geometric "elbow" rule on
    nearest- neighbour distances. It now selects a kernel-density
    bandwidth for each environmental variable using the Sheather-Jones
    plug-in estimator (default), with Silverman and Scott rules also
    available via the new method argument. The bandwidth is a
    statistically defensible choice for the edge length of an
    environmental grid cell, and the new implementation is faster and
    more robust to ties.
  - rgl is now a Suggests dependency rather than an Imports. 3-D plots
    still work when rgl is installed; otherwise plot.bean_ellipsoid()
    falls back to a 2-D view of the first two requested dimensions.
  - The S3 method predict.bean_ellipsoid() is now documented under its
    canonical name (previously the help page was generated as
    predict.ellipsoid_bean).
  - Vignettes have been reorganised:
      - bean-overview — quickstart introduction.
      - data-preparation — preparing rasters and occurrences.
      - environmental-thinning — resolution selection and thinning.
      - niche-modeling — fitting ellipsoids and projecting suitability.
        All vignettes now build without requiring rgl.

CRAN readiness

  - DESCRIPTION: trimmed Imports to MASS, stats, terra; moved rgl,
    ggplot2 and dplyr to Suggests (with dplyr removed entirely from the
    package — it was only used in one vignette).
  - Added a tests/testthat/ test suite covering find_env_resolution(),
    thin_env_nd(), thin_env_center(), fit_ellipsoid() and
    predict.bean_ellipsoid().
  - Datasets are now documented as user-visible (not
    \keyword{internal}).
  - Replaced \dontrun{} examples that depended on missing files with
    \donttest{} examples that use the shipped sample data.
  - prepare_bean() now uses match.arg() for transform.
  - Cleaned up R/globals.R (was carrying many unused identifiers).

Minor

  - print.bean_ellipsoid() output reformatted for clarity.
  - Internal helper .bean_ellipse_polygon() consolidates the 2-D ellipse
    polygon code path used by both fit_ellipsoid() and
    plot.bean_ellipsoid().

                        Changes in version 0.1.2                        

  - Earlier development versions; see commit history on GitHub.