Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models


[Up] [Top]

Documentation for package ‘loo’ version 2.1.0

Help Pages

loo-package Efficient LOO-CV and WAIC for Bayesian models
compare Model comparison
example_loglik_array Objects to use in examples and tests
example_loglik_matrix Objects to use in examples and tests
extract_log_lik Extract pointwise log-likelihood from a Stan model
E_loo Compute weighted expectations
E_loo.default Compute weighted expectations
E_loo.matrix Compute weighted expectations
gpdfit Estimate parameters of the Generalized Pareto distribution
is.kfold Generic function for K-fold cross-validation for developers
is.loo Efficient approximate leave-one-out cross-validation (LOO)
is.psis Pareto smoothed importance sampling (PSIS)
is.psis_loo Efficient approximate leave-one-out cross-validation (LOO)
is.waic Widely applicable information criterion (WAIC)
kfold Generic function for K-fold cross-validation for developers
kfold-generic Generic function for K-fold cross-validation for developers
kfold-helpers Helper functions for K-fold cross-validation
kfold_split_grouped Helper functions for K-fold cross-validation
kfold_split_random Helper functions for K-fold cross-validation
kfold_split_stratified Helper functions for K-fold cross-validation
Kline Datasets for loo examples and vignettes
loo Efficient approximate leave-one-out cross-validation (LOO)
loo-datasets Datasets for loo examples and vignettes
loo-glossary LOO package glossary
loo.array Efficient approximate leave-one-out cross-validation (LOO)
loo.function Efficient approximate leave-one-out cross-validation (LOO)
loo.matrix Efficient approximate leave-one-out cross-validation (LOO)
loo_compare Model comparison
loo_compare.default Model comparison
loo_i Efficient approximate leave-one-out cross-validation (LOO)
loo_model_weights Model averaging/weighting via stacking or pseudo-BMA weighting
loo_model_weights.default Model averaging/weighting via stacking or pseudo-BMA weighting
mcse_loo Diagnostics for Pareto smoothed importance sampling (PSIS)
milk Datasets for loo examples and vignettes
pareto-k-diagnostic Diagnostics for Pareto smoothed importance sampling (PSIS)
pareto_k_ids Diagnostics for Pareto smoothed importance sampling (PSIS)
pareto_k_table Diagnostics for Pareto smoothed importance sampling (PSIS)
pareto_k_values Diagnostics for Pareto smoothed importance sampling (PSIS)
plot.loo Diagnostics for Pareto smoothed importance sampling (PSIS)
plot.psis Diagnostics for Pareto smoothed importance sampling (PSIS)
plot.psis_loo Diagnostics for Pareto smoothed importance sampling (PSIS)
print.compare.loo Model comparison
print.loo Print methods
print.psis Print methods
print.psis_loo Print methods
print.waic Print methods
pseudobma_weights Model averaging/weighting via stacking or pseudo-BMA weighting
psis Pareto smoothed importance sampling (PSIS)
psis.array Pareto smoothed importance sampling (PSIS)
psis.default Pareto smoothed importance sampling (PSIS)
psis.matrix Pareto smoothed importance sampling (PSIS)
psislw Pareto smoothed importance sampling (deprecated, old version)
psis_n_eff_values Diagnostics for Pareto smoothed importance sampling (PSIS)
relative_eff Convenience function for computing relative efficiencies
relative_eff.array Convenience function for computing relative efficiencies
relative_eff.default Convenience function for computing relative efficiencies
relative_eff.function Convenience function for computing relative efficiencies
relative_eff.matrix Convenience function for computing relative efficiencies
stacking_weights Model averaging/weighting via stacking or pseudo-BMA weighting
waic Widely applicable information criterion (WAIC)
waic.array Widely applicable information criterion (WAIC)
waic.function Widely applicable information criterion (WAIC)
waic.matrix Widely applicable information criterion (WAIC)
weights.psis Pareto smoothed importance sampling (PSIS)