Efficient approximate leave-one-out cross-validation (LOO)
for Bayesian models fit using Markov chain Monte Carlo, as described
in Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4>.
The approximation uses 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. The package also provides methods for using
stacking and other model weighting techniques to average Bayesian
predictive distributions.
| Version: |
2.9.0 |
| Depends: |
R (≥ 3.1.2) |
| Imports: |
checkmate, matrixStats (≥ 0.52), parallel, posterior (≥
1.5.0), stats |
| Suggests: |
bayesplot (≥ 1.7.0), brms (≥ 2.10.0), ggplot2, graphics, knitr, rmarkdown, rstan, rstanarm (≥ 2.19.0), rstantools, spdep, testthat (≥ 3.0) |
| Published: |
2025-12-23 |
| DOI: |
10.32614/CRAN.package.loo |
| Author: |
Aki Vehtari [aut],
Jonah Gabry [cre, aut],
Måns Magnusson [aut],
Yuling Yao [aut],
Paul-Christian Bürkner [aut],
Topi Paananen [aut],
Andrew Gelman [aut],
Ben Goodrich [ctb],
Juho Piironen [ctb],
Bruno Nicenboim [ctb],
Leevi Lindgren [ctb],
Visruth Srimath Kandali [ctb] |
| Maintainer: |
Jonah Gabry <jgabry at gmail.com> |
| BugReports: |
https://github.com/stan-dev/loo/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://mc-stan.org/loo/, https://discourse.mc-stan.org |
| NeedsCompilation: |
no |
| SystemRequirements: |
pandoc (>= 1.12.3), pandoc-citeproc |
| Citation: |
loo citation info |
| Materials: |
NEWS |
| In views: |
Bayesian |
| CRAN checks: |
loo results |
| Reverse depends: |
bistablehistory, evidence, spsurv, TriDimRegression |
| Reverse imports: |
BAMBI, bayclumpr, bayesdfa, BayesERtools, bayesforecast, BayesGrowth, BayesianFitForecast, bayesnec, bellreg, bivarhr, blavaan, bmgarch, bmggum, bmscstan, brms, bsitar, causalOT, conformalbayes, disbayes, dynamite, EBcoBART, eDNAjoint, FlexReg, flocker, glmmfields, GPTCM, hbamr, hBayesDM, hdbayes, HeckmanStan, hsstan, LMMELSM, mcmcsae, mcp, measr, MetaStan, missingHE, MixSIAR, multilevelcoda, mvgam, pcFactorStan, phylopairs, projpred, publipha, qbrms, rater, rbioacc, rmsb, rmstBayespara, rstan, rstanarm, rtmpt, serofoi, shinymrp, StanMoMo, survextrap, tsnet, ubms, vacalibration, walker |
| Reverse suggests: |
bayesianOU, bayesplot, bayesvl, bmstdr, BSTFA, expertsurv, footBayes, GUD, multinma, neodistr, performance, redist, report, rPBK, sccomp, tipsae, valueprhr, webSDM |