greta: Simple and Scalable Statistical Modelling in R

Write statistical models in R and fit them by MCMC on CPUs and GPUs, using Google TensorFlow (see <https://greta-dev.github.io/greta> for more information).

Version: 0.3.0
Depends: R (≥ 3.0)
Imports: R6, tensorflow, reticulate, progress (≥ 1.2.0), future, coda, methods
Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice, testthat, mvtnorm, MCMCpack, rmutil, extraDistr, truncdist, tidyverse, fields, MASS, abind
Published: 2018-10-30
Author: Nick Golding ORCID iD [aut, cre], Simon Dirmeier [ctb], Adam Fleischhacker [ctb], Shirin Glander [ctb], Martin Ingram [ctb], Lee Hazel [ctb], Tiphaine Martin [ctb], Matt Mulvahill [ctb], Michael Quinn [ctb], David Smith [ctb], Paul Teetor [ctb], Jian Yen [ctb]
Maintainer: Nick Golding <nick.golding.research at gmail.com>
BugReports: https://github.com/greta-dev/greta/issues
License: Apache License 2.0
URL: https://github.com/greta-dev/greta
NeedsCompilation: no
SystemRequirements: Python (>= 2.7.0) with header files and shared library; TensorFlow (>= 1.10; https://www.tensorflow.org/); Tensorflow Probability (>=0.3.0; https://www.tensorflow.org/probability/)
Materials: NEWS
CRAN checks: greta results

Downloads:

Reference manual: greta.pdf
Vignettes: Example models
Get started with greta
Package source: greta_0.3.0.tar.gz
Windows binaries: r-devel: greta_0.3.0.zip, r-release: greta_0.3.0.zip, r-oldrel: greta_0.3.0.zip
OS X binaries: r-release: greta_0.3.0.tgz, r-oldrel: greta_0.3.0.tgz
Old sources: greta archive

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