Compute weighted expectations
Pareto smoothed importance sampling (PSIS) using approximate posteriors
Model comparison (deprecated, old version)
Continuously ranked probability score
Compute a point estimate from a draws object
The number of posterior draws in a draws object.
Thin a draws object
Generic (expected) log-predictive density
Objects to use in examples and tests
Extract pointwise log-likelihood from a Stan model
Find the model names associated with '"loo"' objects
Estimate parameters of the Generalized Pareto distribution
A parent class for different importance sampling methods.
Importance sampling of array
Importance sampling (default)
Importance sampling of matrices
Generic function for K-fold cross-validation for developers
Helper functions for K-fold cross-validation
Datasets for loo examples and vignettes
LOO package glossary
Efficient LOO-CV and WAIC for Bayesian models
Efficient approximate leave-one-out cross-validation (LOO)
Efficient approximate leave-one-out cross-validation (LOO) for posterior approximations
Model comparison
Model averaging/weighting via stacking or pseudo-BMA weighting
Moment matching for efficient approximate leave-one-out cross-validation (LOO)
Split moment matching for efficient approximate leave-one-out cross-validation (LOO)
Estimate leave-one-out predictive performance..
Efficient approximate leave-one-out cross-validation (LOO) using subsampling
Named lists
The number of observations in a 'psis_loo_ss' object.
Get observation indices used in subsampling
Extractor methods
Parallel psis list computations
Diagnostics for Pareto smoothed importance sampling (PSIS)
Print methods
Print dimensions of log-likelihood or log-weights matrix
Pareto smoothed importance sampling (PSIS)
Diagnostics for Laplace and ADVI approximations and Laplace-loo and ADVI-loo
Pareto smoothed importance sampling (deprecated, old version)
Convenience function for computing relative efficiencies
Standard importance sampling (SIS)
Truncated importance sampling (TIS)
Update 'psis_loo_ss' objects
Widely applicable information criterion (WAIC)
Extract importance sampling weights