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fit_ellipsoid() help page now direct users to
install.packages("nicheR") rather than the previous GitHub
instructions.nicheR is declared in Suggests. The
package itself never calls nicheR — the integration is purely S3
dispatch on the "nicheR_ellipsoid" class — so it does not
belong in Imports.predict() example now
executes when nicheR and terra are both installed
(eval = has_nicheR && has_terra) instead of being
permanently disabled with eval = FALSE.predict.bean_ellipsoid(). The canonical
implementation now lives in the companion package
nicheR.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.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.terra fallback for users who do not yet have nicheR
installed.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.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.predict.bean_ellipsoid() is now
documented under its canonical name (previously the help page was
generated as predict.ellipsoid_bean).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.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).tests/testthat/ test suite covering
find_env_resolution(), thin_env_nd(),
thin_env_center(), fit_ellipsoid() and
predict.bean_ellipsoid().\keyword{internal}).\dontrun{} examples that depended on missing
files with \donttest{} examples that use the shipped sample
data.prepare_bean() now uses match.arg() for
transform.R/globals.R (was carrying many unused
identifiers).print.bean_ellipsoid() output reformatted for
clarity..bean_ellipse_polygon() consolidates
the 2-D ellipse polygon code path used by both
fit_ellipsoid() and
plot.bean_ellipsoid().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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