| AIC.xnicher | Akaike information criterion for a xnicher fit |
| assess | Assess acceptance criteria for an optimization result |
| assess.xnicher | Assess acceptance criteria for a xnicher result |
| BIC.xnicher | Bayesian information criterion for a xnicher fit |
| compare_xnicher | Compare xnicher fits side-by-side via AIC and BIC |
| cvine_cholesky | Build Cholesky factor of a correlation matrix from C‑vine partial correlations |
| cv_xnicher | k-fold (or leave-one-out) cross-validation for a xnicher fit |
| example_env_m_2d | Samples of environmental data from M hypothesis to estimate negative log likelihood from Abeillia abeillei presence points. This is a hummingbird example. A dataset with two variables containing points contains 2 bioclimatic variables |
| example_env_m_3d | Samples points from M hypothesis to estimate negative log likelihood from Abeillia abeillei presence points. This is a hummingbird example. A dataset with three columns containing extracted information from 3 bioclimatic variables |
| example_env_occ_2d | Species occurrence points to estimate negative log likelihood from Abeillia abeillei presence points. This is a hummingbird example. A dataset with two variables containing points contains 2 bioclimatic variables |
| example_env_occ_3d | Species occurrence points to estimate negative log likelihood from Abeillia abeillei presence points. This is a hummingbird example. A dataset with three variables containing points contains 3 bioclimatic variables |
| example_mu_vec | Example of a vector of the center of an ellipsoid from two environmental variables. vector of length 2 corresponding to the centroid of an ellipsoid |
| example_occ_df | Species occurrence points from Abeillia abeillei presence points after download and clean from GBIF. This is a hummingbird example. A dataset with three variables. Contains scientific name, longitude and latitude. |
| example_s_mat | Example of a covariance matrix of an ellipsoid from two environmental variables. The 2 x 2 matrix corresponded to a positive semi-definite matrix. In two dimensions encodes the rotation (orientation) and scaling of an ellipse. |
| example_vicugna | Samples of environmental data from M hypothesis to estimate negative log likelihood from Vicugna vicugna. |
| geom_xnicher_background | Background environment layer |
| geom_xnicher_ellipse | Niche-ellipse layer derived from a fitted 'xnicher' model |
| geom_xnicher_isosuitability | Iso-suitability contour layer derived from a fitted 'xnicher' model |
| geom_xnicher_occ | Occurrence-points layer |
| get_ellipsoid_pars | Get ellipsoid parameters. A function to compute average and the inverse of covariance matrix from environmental data |
| habitat_suitability | Tiled habitat-suitability map from an environmental 'terra' stack |
| kde_gaussian | Multivariate Gaussian KDE with fixed Scott bandwidth |
| logLik.xnicher | Log-likelihood of a fitted xnicher model |
| loglik_niche | Negative log likelihood of an ellipsoid corrected with environmental combinations which come from the area of study (M) |
| loglik_niche_math_cpp | Negative log-likelihood (M-restricted, math scale, Cholesky version) |
| loglik_niche_math_ip_weighted | Negative log-likelihood (inverse-probability-weighted normal, math scale) |
| loglik_niche_math_ip_weighted_integrated | Negative log-likelihood (inverse-probability-weighted normal, integrated C++) |
| loglik_niche_math_presence_only | Negative log-likelihood (presence-only, math scale) |
| niche_ip_weighted | Fit inverse-probability-weighted (IPW) normal niche model |
| niche_presence_only | Fit presence-only Gaussian niche model |
| nobs.xnicher | Number of observations used to fit a xnicher model |
| optimize_niche | Optimize niche model log-likelihood with multi-start Sobol design |
| optimize_niche_xptr | Optimize niche model using a compiled XPtr backend |
| predict.xnicher | Habitat-suitability raster from a fitted 'xnicher' object |
| print.xnicher | Print a xnicher object |
| rhipicephalus | Rhipicephalus microplus occurrence and background environment data |
| rhipicephalus_occ | Rhipicephalus microplus occurrence coordinates |
| start_theta | Starting values for niche model on math scale |
| start_theta_multiple | Generate multiple starting points for niche model optimization |