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) |