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Package: loo
Type: Package
Title: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian
Models
Version: 0.1.6
Date: 2016-03-23
Authors@R: c(person("Aki", "Vehtari", email = "Aki.Vehtari@aalto.fi", role = c("aut")),
person("Andrew", "Gelman", email = "gelman@stat.columbia.edu", role = c("aut")),
person("Jonah", "Gabry", email = "jsg2201@columbia.edu", role = c("cre", "aut")),
person("Juho", "Piironen", role = c("ctb")),
person("Ben", "Goodrich", role = c("ctb")))
Maintainer: Jonah Gabry <jsg2201@columbia.edu>
URL: https://github.com/stan-dev/loo
BugReports: https://github.com/stan-dev/loo/issues
Description: 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).
License: GPL (>= 3)
LazyData: TRUE
Depends: R (>= 3.1.2)
Imports: graphics, matrixStats (>= 0.14.1), parallel, stats
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-03-23 19:19:51 UTC; jgabry
Author: Aki Vehtari [aut],
Andrew Gelman [aut],
Jonah Gabry [cre, aut],
Juho Piironen [ctb],
Ben Goodrich [ctb]
Repository: CRAN
Date/Publication: 2016-03-23 22:29:59
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