Generalised Linear Latent Variable Models

Documentation for package ‘gllvmTMB’ version 0.7.1

Help Pages

-- A --

add_utm_columns	Add UTM coordinates to a data frame
animal_dep	Full unstructured animal-model trait covariance: 'animal_dep(0 + trait \| id)'
animal_indep	Independent per-trait animal-model random intercepts: 'animal_indep(0 + trait \| id)'
animal_latent	Reduced-rank animal-model latent factors: 'animal_latent(id, d = K)'
animal_scalar	Single-shared-variance animal-model random effect: 'animal_scalar(id)'
animal_slope	Animal-model random slope on a continuous covariate
animal_unique	Per-trait independent animal-model random intercepts: 'animal_unique(id)'

-- B --

block_V	Build a block-diagonal sampling-variance matrix V
bootstrap_Sigma	Bootstrap covariance, correlation, communality, and ICC summaries

-- C --

categorical	Baseline-category softmax unordered categorical missing-predictor family
check_auto_residual	Check whether 'link_residual = "auto"' is coherent for this fit
check_gllvmTMB	Check convergence, Hessian, gradients, and interval readiness
coef.gllvmTMB_julia	Methods for Julia bridge fits
coef.gllvmTMB_multi	Fixed-effect estimates and covariance for a multi-trait fit
coef.gllvmTMB_va	Methods for variational ('integration = "va"') fits
compare_dep_vs_two_psi	Canonical likelihood-based cross-check for the paired phylogenetic decomposition
compare_indep_vs_two_psi	Cheap diagonal cross-check for the paired phylogenetic decomposition (large T)
compare_loadings	Compare two loading matrices after Procrustes alignment
compare_Sigma_table	Compare fitted Sigma-table rows with a known truth matrix
confint.gllvmTMB_julia	Methods for Julia bridge fits
confint.gllvmTMB_multi	Confidence intervals for a fitted gllvmTMB model
confint.gllvmTMB_va	Methods for variational ('integration = "va"') fits
confint_inspect	Inspect profile confidence-interval shape for a fitted model
confirmatory_lambda	Build a confirmatory 'lambda_constraint' matrix from group membership
cumulative_logit	Cumulative-logit ordered categorical missing-predictor family

-- D --

dep	Full unstructured trait covariance: 'dep(0 + trait \| g)'
deviance.gllvmTMB_multi	Deviance of a fitted gllvmTMB model
deviance.gllvmTMB_va	Methods for variational ('integration = "va"') fits
df.residual.gllvmTMB_va	Methods for variational ('integration = "va"') fits
diagnose_kernel_separability	Diagnose fixed-kernel separability before fitting
diagnostic_table	Extract report-ready tables from diagnostic objects

-- E --

extract_coevolution_modules	Extract cross-lineage coevolutionary modules
extract_communality	Communality of each trait
extract_correlations	Extract cross-trait correlations
extract_cross_correlations	Cross-family correlations between a nominal (multinomial) trait and partners
extract_cutpoints	Extract ordinal-probit cutpoints from a fitted gllvmTMB model
extract_Gamma	Extract a cross-lineage Gamma block
extract_loadings	Extract the trait loading matrix
extract_lv_effects	Predictor effects on latent-score means
extract_Omega	Total trait covariance Omega summed across requested tiers
extract_ordination	Extract ordination scores and loadings from a fitted multivariate model
extract_phylo_signal	Phylogenetic-signal proportions per trait
extract_proportions	Per-trait proportion-of-variance decomposition across all model components
extract_repeatability	Per-trait repeatability with confidence intervals
extract_residual_cor	Implied trait covariance or correlation
extract_residual_cov	Implied trait covariance or correlation
extract_rotated_loadings_table	Extract a tidy rotated loading table
extract_Sigma	Extract the implied trait covariance / correlation at one tier
extract_Sigma_table	Extract a report-ready table of Sigma or correlation entries

-- F --

fitted.gllvmTMB_julia	Methods for Julia bridge fits
fitted.gllvmTMB_multi	Fitted values from a fitted gllvmTMB model
fitted.gllvmTMB_va	Methods for variational ('integration = "va"') fits
flag_unreliable_loadings	Flag loadings whose CI overlaps a "biologically negligible" region

-- G --

get_crs	Infer a UTM coordinate reference system
gllvmTMB	Fit multivariate response models from wide or long data
gllvmTMBcontrol	Control parameters for 'gllvmTMB()'
gllvmTMB_check_consistency	Run an advanced Laplace-consistency check
gllvmTMB_diagnose	Diagnose a fitted model and suggest next actions
gllvmTMB_julia-methods	Methods for Julia bridge fits
gllvmTMB_multi-methods	Methods on a fitted gllvmTMB model
gllvmTMB_multi-vcov	Fixed-effect estimates and covariance for a multi-trait fit
gllvmTMB_va-methods	Methods for variational ('integration = "va"') fits
gllvm_julia_fit	Fit a GLLVM with the Julia engine (GLLVM.jl 'bridge_fit').
gllvm_julia_setup	Set up JuliaCall and load the GLLVM.jl engine (once per R session).

-- I --

imputed	Extract fitted missing-predictor values from a 'gllvmTMB' fit
imputed.gllvmTMB	Extract fitted missing-predictor values from a 'gllvmTMB' fit
impute_model	Predictor model for a missing covariate used inside 'mi()'
indep	Per-trait marginal variance: 'indep(0 + trait \| g)'
isdm_source	Declare one iSDM source observation model
isdm_sources	Declare the sources of a multi-source integrated model

-- K --

kernel_dep	Generic dense-kernel covariance keywords
kernel_indep	Generic dense-kernel covariance keywords
kernel_latent	Generic dense-kernel covariance keywords
kernel_scalar	Dense-kernel one-shared-variance covariance: 'kernel_scalar()'
kernel_unique	Deprecated alias: 'kernel_unique()'

-- L --

latent	Latent-factor (reduced-rank) random effect: 'latent(0 + trait \| g, d = K)'
loading_ci	Confidence intervals on individual entries of the loading matrix
loading_profile	Profile-likelihood curve(s) for entries of the loading matrix
logLik.gllvmTMB_julia	Methods for Julia bridge fits
logLik.gllvmTMB_multi	Methods on a fitted gllvmTMB model
logLik.gllvmTMB_va	Methods for variational ('integration = "va"') fits

-- M --

make_cross_kernel	Build a cross-lineage relatedness kernel
make_mesh	Construct an SPDE mesh for gllvmTMB
meta_V	Known-V meta-analytic random effect (canonical name): 'meta_V(V = V)'
mi	Predictor model for a missing covariate used inside 'mi()'
miss_control	Missing-data control for 'gllvmTMB()'
mi_group	Predictor model for a missing covariate used inside 'mi()'
multinomial	Multinomial (baseline-category logit) family

-- N --

nobs.gllvmTMB_multi	Methods on a fitted gllvmTMB model
nobs.gllvmTMB_va	Methods for variational ('integration = "va"') fits

-- O --

ordinal_probit

Ordinal-probit threshold family for the multivariate engine

-- P --

pedigree_to_A	Pedigree to additive-genetic relatedness matrix 'A'
pedigree_to_Ainv_sparse	Sparse pedigree inverse-A via Henderson-Quaas (MCMCglmm-free)
phylo	Phylogenetic random effect: lme4-bar mode-dispatch wrapper
phylo_dep	Full unstructured phylogenetic trait covariance: 'phylo_dep(0 + trait \| species)'
phylo_indep	Per-trait phylogenetic marginal variance: 'phylo_indep(0 + trait \| species)'
phylo_latent	Reduced-rank phylogenetic latent factors: 'phylo_latent(species, d = K)'
phylo_scalar	Single-shared-variance phylogenetic random effect: 'phylo_scalar(species)'
phylo_signal_mi	Phylogenetic-signal diagnostic for a modelled missing predictor
phylo_slope	Phylogenetic random slope on a continuous covariate
phylo_unique	Per-trait independent phylogenetic random intercepts: 'phylo_unique(species)'
plot.gllvmTMBmesh	Plot a gllvmTMB SPDE mesh
plot.gllvmTMB_multi	Plot a fitted multivariate gllvmTMB model
plot.profile_derived	Plot a profile-derived LR curve
plot.profile_loadings	Plot a profile_loadings object (LR U-shape per entry)
plot.sdmTMBmesh	Plot a gllvmTMB SPDE mesh
plot_anisotropy	Plot the isotropic spatial range from a gllvmTMB model
plot_anisotropy2	Plot the isotropic spatial range from a gllvmTMB model
plot_correlations	Plot pairwise trait correlations with intervals
plot_loadings_confidence_eye	Confidence Eye plot for per-species loading uncertainty
plot_rotated_loadings	Plot a rotated loading matrix
plot_Sigma_comparison	Plot Sigma-table estimates against a known truth matrix
plot_Sigma_heatmap	Plot Sigma-table rows as a trait-by-trait heatmap
plot_Sigma_table	Plot report-ready Sigma table rows
predict.gllvmTMB_julia	Methods for Julia bridge fits
predict.gllvmTMB_multi	Predict from a fitted gllvmTMB model
predict.gllvmTMB_va	Methods for variational ('integration = "va"') fits
predictive_check	Fitted-model predictive checks for a multivariate 'gllvmTMB' fit
predict_cross_covariance	Predict pair-specific cross-lineage covariance
predict_missing	Predict the masked (missing) response cells of a gllvmTMB fit
print.gllvmTMB_julia	Methods for Julia bridge fits
print.gllvmTMB_multi	Methods on a fitted gllvmTMB model
print.gllvmTMB_Sigma_phy_slope	Print an augmented latent-slope Sigma extraction
print.gllvmTMB_va	Methods for variational ('integration = "va"') fits
print.summary.gllvmTMB_julia	Methods for Julia bridge fits
print.summary.gllvmTMB_multi	Methods on a fitted gllvmTMB model
print.summary.gllvmTMB_va	Methods for variational ('integration = "va"') fits
profile_ci_total_variance	Profile-likelihood CI for per-trait total variance
profile_cross_rho	Profile fixed cross-lineage rho values
profile_cross_rho_ci	Profile sensitivity interval for the cross-lineage 'rho'
profile_phylo_signal	Profile-likelihood curve(s) for per-trait phylogenetic signal
profile_targets	List profile-ready confidence-interval targets for a fitted model

-- R --

residuals.gllvmTMB_julia	Methods for Julia bridge fits
residuals.gllvmTMB_multi	Diagnostic residuals for a multivariate 'gllvmTMB' fit
residuals.gllvmTMB_va	Methods for variational ('integration = "va"') fits
ridge_path	Sweep the loading-ridge penalty and report a stability path
rotate_loadings	Rotate the loadings of a fitted multivariate model

-- S --

sanity_multi	Print a quick convergence and parameter sanity report
scalar	One shared trait variance: 'scalar(0 + trait \| g)'
screen_control	Control pre-fit response screening
screen_gllvmTMB	Screen candidate responses before fitting a gllvmTMB model
screen_table	Extract tables from a pre-fit screen
simulate.gllvmTMB_julia	Methods for Julia bridge fits
simulate.gllvmTMB_multi	Simulate new responses from a fitted gllvmTMB model
simulate_site_trait	Simulate a functional-biogeography GLLVM dataset (sites × species × traits)
simulate_unit_trait	Simulate a generic stacked-trait GLLVM dataset (units x observations x traits)
slope_sd_ci	Wald confidence intervals on augmented random-slope standard deviations
spatial	Spatial random field: lme4-bar mode-dispatch wrapper
spatial_dep	Full unstructured spatial trait covariance: 'spatial_dep(0 + trait \| coords)'
spatial_indep	Per-trait spatial marginal field: 'spatial_indep(0 + trait \| coords)'
spatial_latent	Reduced-rank spatial latent factors: 'spatial_latent(0 + trait \| coords, d = K)'
spatial_scalar	Deprecated alias for one shared spatial-field variance
spatial_unique	Per-trait independent spatial random fields: 'spatial_unique(0 + trait \| coords)'
standard_errors	Compute standard errors after fitting
suggest_lambda_constraint	Suggest a 'lambda_constraint' matrix for a reduced-rank fit
suggest_lambda_constraints	Compare several 'lambda_constraint' suggestions
summary.gllvmTMB_julia	Methods for Julia bridge fits
summary.gllvmTMB_multi	Methods on a fitted gllvmTMB model
summary.gllvmTMB_va	Methods for variational ('integration = "va"') fits

-- T --

tidy.gllvmTMB_multi	Tidy a fitted gllvmTMB model
traits	Wide-format trait marker for the 'gllvmTMB()' formula LHS

-- V --

vcov.gllvmTMB_multi	Fixed-effect estimates and covariance for a multi-trait fit
vcov.gllvmTMB_va	Methods for variational ('integration = "va"') fits

-- W --

weights.gllvmTMB_va

Methods for variational ('integration = "va"') fits