Package: greta
Type: Package
Title: Simple and Scalable Statistical Modelling in R
Version: 0.2.0
Date: 2017-06-26
Authors@R: person("Nick", "Golding", role = c("aut", "cre"),
    email = "nick.golding.research@gmail.com")
Description: 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).
License: Apache License 2.0
URL: https://github.com/goldingn/greta
BugReports: https://github.com/goldingn/greta/issues
SystemRequirements: Python (>= 2.7.0) with header files and shared
        library; TensorFlow (>= 1.0.0; https://www.tensorflow.org/)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0)
Collate: 'package.R' 'overloaded.R' 'node_class.R' 'node_types.R'
        'variable.R' 'probability_distributions.R' 'unknowns_class.R'
        'greta_array_class.R' 'as_data.R' 'utils.R' 'distribution.R'
        'operators.R' 'functions.R' 'transforms.R' 'structures.R'
        'extract_replace_combine.R' 'dynamics_module.R' 'dag_class.R'
        'greta_model_class.R' 'progress_bar.R' 'inference.R'
        'samplers.R' 'install_tensorflow.R'
Imports: R6, tensorflow, reticulate, progress, coda
Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice, testthat,
        mvtnorm, MCMCpack, rmutil, extraDistr, truncdist
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-26 13:19:19 UTC; nick
Author: Nick Golding [aut, cre]
Maintainer: Nick Golding <nick.golding.research@gmail.com>
Repository: CRAN
Date/Publication: 2017-06-26 13:57:01 UTC
