| Add UTM coordinates to a data frame | add_utm_columns |
| Full unstructured animal-model trait covariance: 'animal_dep(0 + trait | id)' | animal_dep |
| Independent per-trait animal-model random intercepts: 'animal_indep(0 + trait | id)' | animal_indep |
| Reduced-rank animal-model latent factors: 'animal_latent(id, d = K)' | animal_latent |
| Single-shared-variance animal-model random effect: 'animal_scalar(id)' | animal_scalar |
| Animal-model random slope on a continuous covariate | animal_slope |
| Per-trait independent animal-model random intercepts: 'animal_unique(id)' | animal_unique |
| Build a block-diagonal sampling-variance matrix V | block_V |
| Bootstrap covariance, correlation, communality, and ICC summaries | bootstrap_Sigma |
| Baseline-category softmax unordered categorical missing-predictor family | categorical |
| Check whether 'link_residual = "auto"' is coherent for this fit | check_auto_residual |
| Check convergence, Hessian, gradients, and interval readiness | check_gllvmTMB |
| Canonical likelihood-based cross-check for the paired phylogenetic decomposition | compare_dep_vs_two_psi |
| Cheap diagonal cross-check for the paired phylogenetic decomposition (large T) | compare_indep_vs_two_psi |
| Compare two loading matrices after Procrustes alignment | compare_loadings |
| Compare fitted Sigma-table rows with a known truth matrix | compare_Sigma_table |
| Inspect profile confidence-interval shape for a fitted model | confint_inspect |
| Confidence intervals for a fitted gllvmTMB model | confint.gllvmTMB_multi |
| Build a confirmatory 'lambda_constraint' matrix from group membership | confirmatory_lambda |
| Cumulative-logit ordered categorical missing-predictor family | cumulative_logit |
| Full unstructured trait covariance: 'dep(0 + trait | g)' | dep |
| Deviance of a fitted gllvmTMB model | deviance.gllvmTMB_multi |
| Diagnose fixed-kernel separability before fitting | diagnose_kernel_separability |
| Extract report-ready tables from diagnostic objects | diagnostic_table |
| Extract cross-lineage coevolutionary modules | extract_coevolution_modules |
| Communality of each trait | extract_communality |
| Extract cross-trait correlations | extract_correlations |
| Cross-family correlations between a nominal (multinomial) trait and partners | extract_cross_correlations |
| Extract ordinal-probit cutpoints from a fitted gllvmTMB model | extract_cutpoints |
| Extract a cross-lineage Gamma block | extract_Gamma |
| Extract the trait loading matrix | extract_loadings |
| Predictor effects on latent-score means | extract_lv_effects |
| Total trait covariance Omega summed across requested tiers | extract_Omega |
| Extract ordination scores and loadings from a fitted multivariate model | extract_ordination |
| Phylogenetic-signal proportions per trait | extract_phylo_signal |
| Per-trait proportion-of-variance decomposition across all model components | extract_proportions |
| Per-trait repeatability with confidence intervals | extract_repeatability |
| Implied trait covariance or correlation | extract_residual_cor extract_residual_cov |
| Extract a tidy rotated loading table | extract_rotated_loadings_table |
| Extract the implied trait covariance / correlation at one tier | extract_Sigma |
| Extract a report-ready table of Sigma or correlation entries | extract_Sigma_table |
| Fitted values from a fitted gllvmTMB model | fitted.gllvmTMB_multi |
| Flag loadings whose CI overlaps a "biologically negligible" region | flag_unreliable_loadings |
| Infer a UTM coordinate reference system | get_crs |
| Fit a GLLVM with the Julia engine (GLLVM.jl 'bridge_fit'). | gllvm_julia_fit |
| Set up JuliaCall and load the GLLVM.jl engine (once per R session). | gllvm_julia_setup |
| Fit multivariate response models from wide or long data | gllvmTMB |
| Run an advanced Laplace-consistency check | gllvmTMB_check_consistency |
| Diagnose a fitted model and suggest next actions | gllvmTMB_diagnose |
| Methods for Julia bridge fits | coef.gllvmTMB_julia confint.gllvmTMB_julia fitted.gllvmTMB_julia gllvmTMB_julia-methods logLik.gllvmTMB_julia predict.gllvmTMB_julia print.gllvmTMB_julia print.summary.gllvmTMB_julia residuals.gllvmTMB_julia simulate.gllvmTMB_julia summary.gllvmTMB_julia |
| Methods on a fitted gllvmTMB model | gllvmTMB_multi-methods logLik.gllvmTMB_multi nobs.gllvmTMB_multi print.gllvmTMB_multi print.summary.gllvmTMB_multi summary.gllvmTMB_multi |
| Fixed-effect estimates and covariance for a multi-trait fit | coef.gllvmTMB_multi gllvmTMB_multi-vcov vcov.gllvmTMB_multi |
| Methods for variational ('integration = "va"') fits | coef.gllvmTMB_va confint.gllvmTMB_va deviance.gllvmTMB_va df.residual.gllvmTMB_va fitted.gllvmTMB_va gllvmTMB_va-methods logLik.gllvmTMB_va nobs.gllvmTMB_va predict.gllvmTMB_va print.gllvmTMB_va print.summary.gllvmTMB_va residuals.gllvmTMB_va summary.gllvmTMB_va vcov.gllvmTMB_va weights.gllvmTMB_va |
| Control parameters for 'gllvmTMB()' | gllvmTMBcontrol |
| Predictor model for a missing covariate used inside 'mi()' | impute_model mi mi_group |
| Extract fitted missing-predictor values from a 'gllvmTMB' fit | imputed imputed.gllvmTMB |
| Per-trait marginal variance: 'indep(0 + trait | g)' | indep |
| Declare one iSDM source observation model | isdm_source |
| Declare the sources of a multi-source integrated model | isdm_sources |
| Generic dense-kernel covariance keywords | kernel_dep kernel_indep kernel_latent |
| Dense-kernel one-shared-variance covariance: 'kernel_scalar()' | kernel_scalar |
| Deprecated alias: 'kernel_unique()' | kernel_unique |
| Latent-factor (reduced-rank) random effect: 'latent(0 + trait | g, d = K)' | latent |
| Confidence intervals on individual entries of the loading matrix | loading_ci |
| Profile-likelihood curve(s) for entries of the loading matrix | loading_profile |
| Build a cross-lineage relatedness kernel | make_cross_kernel |
| Construct an SPDE mesh for gllvmTMB | make_mesh |
| Known-V meta-analytic random effect (canonical name): 'meta_V(V = V)' | meta_V |
| Missing-data control for 'gllvmTMB()' | miss_control |
| Multinomial (baseline-category logit) family | multinomial |
| Ordinal-probit threshold family for the multivariate engine | ordinal_probit |
| Pedigree to additive-genetic relatedness matrix 'A' | pedigree_to_A |
| Sparse pedigree inverse-A via Henderson-Quaas (MCMCglmm-free) | pedigree_to_Ainv_sparse |
| Phylogenetic random effect: lme4-bar mode-dispatch wrapper | phylo |
| Full unstructured phylogenetic trait covariance: 'phylo_dep(0 + trait | species)' | phylo_dep |
| Per-trait phylogenetic marginal variance: 'phylo_indep(0 + trait | species)' | phylo_indep |
| Reduced-rank phylogenetic latent factors: 'phylo_latent(species, d = K)' | phylo_latent |
| Single-shared-variance phylogenetic random effect: 'phylo_scalar(species)' | phylo_scalar |
| Phylogenetic-signal diagnostic for a modelled missing predictor | phylo_signal_mi |
| Phylogenetic random slope on a continuous covariate | phylo_slope |
| Per-trait independent phylogenetic random intercepts: 'phylo_unique(species)' | phylo_unique |
| Plot the isotropic spatial range from a gllvmTMB model | plot_anisotropy plot_anisotropy2 |
| Plot pairwise trait correlations with intervals | plot_correlations |
| Confidence Eye plot for per-species loading uncertainty | plot_loadings_confidence_eye |
| Plot a rotated loading matrix | plot_rotated_loadings |
| Plot Sigma-table estimates against a known truth matrix | plot_Sigma_comparison |
| Plot Sigma-table rows as a trait-by-trait heatmap | plot_Sigma_heatmap |
| Plot report-ready Sigma table rows | plot_Sigma_table |
| Plot a fitted multivariate gllvmTMB model | plot.gllvmTMB_multi |
| Plot a gllvmTMB SPDE mesh | plot.gllvmTMBmesh plot.sdmTMBmesh |
| Plot a profile-derived LR curve | plot.profile_derived |
| Plot a profile_loadings object (LR U-shape per entry) | plot.profile_loadings |
| Predict pair-specific cross-lineage covariance | predict_cross_covariance |
| Predict the masked (missing) response cells of a gllvmTMB fit | predict_missing |
| Predict from a fitted gllvmTMB model | predict.gllvmTMB_multi |
| Fitted-model predictive checks for a multivariate 'gllvmTMB' fit | predictive_check |
| Print an augmented latent-slope Sigma extraction | print.gllvmTMB_Sigma_phy_slope |
| Profile-likelihood CI for per-trait total variance | profile_ci_total_variance |
| Profile fixed cross-lineage rho values | profile_cross_rho |
| Profile sensitivity interval for the cross-lineage 'rho' | profile_cross_rho_ci |
| Profile-likelihood curve(s) for per-trait phylogenetic signal | profile_phylo_signal |
| List profile-ready confidence-interval targets for a fitted model | profile_targets |
| Diagnostic residuals for a multivariate 'gllvmTMB' fit | residuals.gllvmTMB_multi |
| Sweep the loading-ridge penalty and report a stability path | ridge_path |
| Rotate the loadings of a fitted multivariate model | rotate_loadings |
| Print a quick convergence and parameter sanity report | sanity_multi |
| One shared trait variance: 'scalar(0 + trait | g)' | scalar |
| Control pre-fit response screening | screen_control |
| Screen candidate responses before fitting a gllvmTMB model | screen_gllvmTMB |
| Extract tables from a pre-fit screen | screen_table |
| Simulate a functional-biogeography GLLVM dataset (sites × species × traits) | simulate_site_trait |
| Simulate a generic stacked-trait GLLVM dataset (units x observations x traits) | simulate_unit_trait |
| Simulate new responses from a fitted gllvmTMB model | simulate.gllvmTMB_multi |
| Wald confidence intervals on augmented random-slope standard deviations | slope_sd_ci |
| Spatial random field: lme4-bar mode-dispatch wrapper | spatial |
| Full unstructured spatial trait covariance: 'spatial_dep(0 + trait | coords)' | spatial_dep |
| Per-trait spatial marginal field: 'spatial_indep(0 + trait | coords)' | spatial_indep |
| Reduced-rank spatial latent factors: 'spatial_latent(0 + trait | coords, d = K)' | spatial_latent |
| Deprecated alias for one shared spatial-field variance | spatial_scalar |
| Per-trait independent spatial random fields: 'spatial_unique(0 + trait | coords)' | spatial_unique |
| Compute standard errors after fitting | standard_errors |
| Suggest a 'lambda_constraint' matrix for a reduced-rank fit | suggest_lambda_constraint |
| Compare several 'lambda_constraint' suggestions | suggest_lambda_constraints |
| Tidy a fitted gllvmTMB model | tidy.gllvmTMB_multi |
| Wide-format trait marker for the 'gllvmTMB()' formula LHS | traits |
