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

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Efficient approximate leave-one-out cross-validation (LOO) using Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. We also compute the widely applicable information criterion (WAIC).

Author
Aki Vehtari [aut], Andrew Gelman [aut], Jonah Gabry [cre, aut], Juho Piironen [ctb], Ben Goodrich [ctb]
Date of publication
2016-03-23 22:29:59
Maintainer
Jonah Gabry <jsg2201@columbia.edu>
License
GPL (>= 3)
Version
0.1.6
URLs

View on CRAN

Man pages

compare
Model comparison
extract_log_lik
Extract log-likelihood from a Stan model
gpdfit
Generalized Pareto distribution
loo
Leave-one-out cross-validation (LOO)
loo-package
Efficient LOO and WAIC for Bayesian models
nlist
Named lists
print.loo
Print and plot methods
psislw
Pareto smoothed importance sampling (PSIS)
waic
Widely applicable information criterion (WAIC)

Files in this package

loo
loo/inst
loo/inst/CITATION
loo/inst/doc
loo/inst/doc/Example.R
loo/inst/doc/Example.Rmd
loo/inst/doc/Example.html
loo/tests
loo/tests/testthat.R
loo/tests/testthat
loo/tests/testthat/test_compare.R
loo/tests/testthat/test_psislw.R
loo/tests/testthat/test_extract_log_lik.R
loo/tests/testthat/test_helpers.R
loo/tests/testthat/test_print_plot.R
loo/tests/testthat/test_loo_and_waic.R
loo/tests/testthat/test_gpdfit.R
loo/NAMESPACE
loo/R
loo/R/gpdfit.R
loo/R/extract_log_lik.R
loo/R/helpers.R
loo/R/waic.R
loo/R/loo.R
loo/R/print.R
loo/R/loo_package.R
loo/R/psislw.R
loo/R/compare.R
loo/R/zzz.R
loo/vignettes
loo/vignettes/Example.Rmd
loo/MD5
loo/build
loo/build/vignette.rds
loo/DESCRIPTION
loo/man
loo/man/loo.Rd
loo/man/loo-package.Rd
loo/man/psislw.Rd
loo/man/waic.Rd
loo/man/print.loo.Rd
loo/man/nlist.Rd
loo/man/compare.Rd
loo/man/extract_log_lik.Rd
loo/man/gpdfit.Rd