dot-resolve_weighted_inputs: Resolve KDE subsampling indices and precompute KDE weights...
In xnicher: Estimates Ecological Niche Models Using Ellipses
.resolve_weighted_inputs R Documentation
Resolve KDE subsampling indices and precompute KDE weights ONCE per fit.
Description
Implements the package's KDE sampling policy:
Hard cap of 10000 distinct background combinations.
Heuristic minimum representative sample of
max(500, 50 * 2^p) rows; below this a warning() is fired.
Optional fraction (x < 1) or integer count for
m_subsample / m_kde_subsample.
Usage
.resolve_weighted_inputs(
env_occ,
env_m,
m_subsample = NULL,
m_kde_subsample = NULL,
seed = NULL
)
Details
Returns a list with: den_idx, kde_idx, w_occ,
w_den, n_m.
xnicher documentation built on Sept. 15, 2026, 5:08 p.m.
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| .resolve_weighted_inputs | R Documentation |
Resolve KDE subsampling indices and precompute KDE weights ONCE per fit.
Description
Implements the package's KDE sampling policy:
Hard cap of 10000 distinct background combinations.
Heuristic minimum representative sample of
max(500, 50 * 2^p)rows; below this awarning()is fired.Optional fraction (
x < 1) or integer count form_subsample/m_kde_subsample.
Usage
.resolve_weighted_inputs(
env_occ,
env_m,
m_subsample = NULL,
m_kde_subsample = NULL,
seed = NULL
)
Details
Returns a list with: den_idx, kde_idx, w_occ,
w_den, n_m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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