Package index • nicheR

All functions

add_data(): Add occurrence points or other data to an existing E-space plot
add_ellipsoid(): Add an ellipsoid boundary to an existing E-space plot
apply_bias(): Apply sampling bias to suitability surfaces
back_data: Background environmental data for examples
build_ellipsoid(): Build a probabilistic ellipsoidal niche from ranges
conserved_ellipses(): Generate ellipses via multivariate normal biased sampling
covariance_limits(): Calculate safe covariance ranges for positive definiteness
ellipsoid_calculator(): Calculate n-dimensional ellipsoid metrics
ellipsoid_volume(): Compute ellipsoid hypervolume
ma_bios: Bioclimatic variables for part of the Americas
nested_ellipses(): Generate nested ellipses based on a reference ellipse
plot_community(): Plot a nicheR Community of Ellipses
plot_ellipsoid(): Plot a nicheR ellipsoid in environmental space
plot_ellipsoid_pairs(): Plot all pairwise 2D ellipsoid projections
predict(<nicheR_community>): Predict method for a nicheR Community
predict(<nicheR_ellipsoid>): Predict suitability and Mahalanobis distance from a nicheR ellipsoid
prepare_bias(): Prepare sampling bias surfaces
print(<nicheR_community>): Print a nicheR Community Object
print(<nicheR_ellipsoid>): Print a nicheR Ellipsoid Object
random_ellipses(): Generate random ellipses constrained by a point cloud and a reference ellipse
ranges_from_data() ranges_from_stats(): Compute variable ranges from data or statistics with optional expansion
read_nicheR(): Read a nicheR object from disk
ref_ellipse: Reference ellipse for virtual community examples
sample_biased_data(): Sample occurrence data from a bias-weighted prediction surface
sample_data(): Sample occurrence data from a prediction surface
sample_virtual_data(): Sample occurrence data from a virtual prediction surface
save_nicheR(): Save a nicheR object to disk
update_covariance(): Update covariance values and calculate remaining safe limits
update_ellipsoid_covariance(): Update covariances in a nicheR ellipsoid and recompute metrics
virtual_data(): Generate data based on a ellipsoidal niche