Package: greta
Type: Package
Title: Simple and Scalable Statistical Modelling in R
Version: 0.3.1
Date: 2019-08-08
Authors@R: c(
  person("Nick", "Golding", role = c("aut", "cre"),
         email = "nick.golding.research@gmail.com",
         comment = c(ORCID = "0000-0001-8916-5570")),
  person("Simon", "Dirmeier", role = "ctb"),
  person("Adam", "Fleischhacker", role = "ctb"),
  person("Shirin", "Glander", role = "ctb"),
  person("Martin", "Ingram", role = "ctb"),
  person("Lee", "Hazel", role = "ctb"),
  person("Tiphaine", "Martin", role = "ctb"),
  person("Matt", "Mulvahill", role = "ctb"),
  person("Michael", "Quinn", role = "ctb"),
  person("David", "Smith", role = "ctb"),
  person("Paul", "Teetor", role = "ctb"),
  person("Jian", "Yen", role = "ctb")
  )
Description: Write statistical models in R and fit them by MCMC and optimisation on CPUs and GPUs, using Google 'TensorFlow'.
  greta lets you write your own model like in BUGS, JAGS and Stan, except that you write models right in R, it scales well to massive datasets, and it’s easy to extend and build on.
  See the website for more information, including tutorials, examples, package documentation, and the greta forum.
License: Apache License 2.0
URL: https://greta-stats.org
BugReports: https://github.com/greta-dev/greta/issues
SystemRequirements: Python (>= 2.7.0) with header files and shared
        library; TensorFlow (v1.14; https://www.tensorflow.org/);
        TensorFlow Probability (v0.7.0;
        https://www.tensorflow.org/probability/)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0)
Collate: 'package.R' 'utils.R' 'tf_functions.R' 'overloaded.R'
        'node_class.R' 'node_types.R' 'variable.R'
        'probability_distributions.R' 'mixture.R' 'joint.R'
        'unknowns_class.R' 'greta_array_class.R' 'as_data.R'
        'distribution.R' 'operators.R' 'functions.R' 'transforms.R'
        'structures.R' 'extract_replace_combine.R' 'dag_class.R'
        'greta_model_class.R' 'progress_bar.R' 'inference_class.R'
        'samplers.R' 'optimisers.R' 'inference.R'
        'install_tensorflow.R' 'internals.R' 'calculate.R'
        'callbacks.R'
Imports: R6, tensorflow (>= 1.13.0), reticulate, progress (>= 1.2.0),
        future, coda, methods
Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice, testthat,
        mvtnorm, MCMCpack, rmutil, extraDistr, truncdist, tidyverse,
        fields, MASS, abind, spelling
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-GB
NeedsCompilation: no
Packaged: 2019-08-09 02:38:06 UTC; nick
Author: Nick Golding [aut, cre] (<https://orcid.org/0000-0001-8916-5570>),
  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@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 04:40:03 UTC
Built: R 4.0.2; ; 2020-08-02 12:15:15 UTC; windows
