DESCRIPTION

Type: Package
Package: greta
Title: Simple and 'Scalable' Statistical Modelling in R
Version: 0.6.0.9000
Authors@R: c(
    person("Nick", "Golding", , "nick.golding.research@gmail.com", role = c("aut", "cph"),
           comment = c(ORCID = "0000-0001-8916-5570")),
    person("Nicholas", "Tierney", , "nicholas.tierney@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "https://orcid.org/0000-0003-1460-8722")),
    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("Lionel", "Hertzog", 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.
    This work is discussed at Golding (2019) <doi:10.21105/joss.01601>.
License: Apache License 2.0
URL: https://greta-dev.github.io/greta/, https://github.com/greta-dev/greta
BugReports: https://github.com/greta-dev/greta/issues
Depends:
    R (>= 4.1.0)
Imports:
    abind,
    callr,
    cli (>= 3.4.1),
    coda,
    future (>= 1.22.1),
    glue (>= 1.5.1),
    lifecycle,
    methods,
    parallelly (>= 1.29.0),
    progress (>= 1.2.0),
    R6,
    reticulate (>= 1.43.0),
    rlang,
    tensorflow (>= 2.16.0),
    tools,
    utils,
    whisker,
    yesno
Suggests:
    bayesplot,
    covr,
    cramer,
    DiagrammeR,
    dplyr,
    DiagrammeRsvg,
    extraDistr,
    fields,
    ggplot2,
    knitr,
    lattice,
    MASS,
    MCMCpack,
    mockery,
    mvtnorm,
    purrr,
    rmarkdown,
    rmutil,
    rsvg,
    spelling,
    testthat (>= 3.1.0),
    tibble,
    tidyr,
    truncdist,
    withr,
    rstudioapi
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
SystemRequirements: Python (>= 3.7.0) with header files and shared
    library; TensorFlow (>= v2.0.0; https://www.tensorflow.org/); TensorFlow
    Probability (v0.8.0; https://www.tensorflow.org/probability/)
Collate:
    'package.R'
    'utils.R'
    'greta_mcmc_list.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'
    'data-deps-tf-tfp.R'
    'greta_model_class.R'
    'progress_bar.R'
    'inference_class.R'
    'samplers.R'
    'sampler_class.R'
    'optimisers.R'
    'optimiser_class.R'
    'inference.R'
    'install_tensorflow.R'
    'calculate.R'
    'callbacks.R'
    'simulate.R'
    'chol2symm.R'
    'install_greta_deps.R'
    'conda_greta_env.R'
    'python_backend.R'
    'greta_stash.R'
    'greta_create_conda_env.R'
    'greta_install_miniconda.R'
    'greta_install_python_deps.R'
    'new_install_process.R'
    'reinstallers.R'
    'checkers.R'
    'test_if_forked_cluster.R'
    'testthat-helpers.R'
    'write-logfiles.R'
    'zzz.R'
    'internals.R'
    'greta-sitrep.R'
LazyData: true
Config/roxygen2/version: 8.0.0