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://goldingn.github.io/greta> for more information).

Version: 0.2.0
Depends: R (≥ 3.0)
Imports: R6, tensorflow, reticulate, progress, coda
Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice, testthat, mvtnorm, MCMCpack, rmutil, extraDistr, truncdist
Published: 2017-06-26
Author: Nick Golding [aut, cre]
Maintainer: Nick Golding <nick.golding.research at gmail.com>
BugReports: https://github.com/goldingn/greta/issues
License: Apache License 2.0
URL: https://github.com/goldingn/greta
NeedsCompilation: no
SystemRequirements: Python (>= 2.7.0) with header files and shared library; TensorFlow (>= 1.0.0; https://www.tensorflow.org/)
CRAN checks: greta results

Downloads:

Reference manual: greta.pdf
Vignettes: Example models
Get started with greta
Technical details
Package source: greta_0.2.0.tar.gz
Windows binaries: r-devel: greta_0.2.0.zip, r-release: greta_0.2.0.zip, r-oldrel: greta_0.2.0.zip
OS X El Capitan binaries: r-release: greta_0.2.0.tgz
OS X Mavericks binaries: r-oldrel: greta_0.2.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=greta to link to this page.