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Merge pull request #79 from goldingn/dev
v0.2.0 candidate
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@@ -14,7 +14,7 @@ r_packages: | |
- knitr | ||
- rmarkdown | ||
- rsvg | ||
- MCMCvis | ||
- bayesplot | ||
- extraDistr | ||
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||
r_github_packages: | ||
|
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@@ -1,22 +1,11 @@ | ||
Package: greta | ||
Type: Package | ||
Title: Probabilistic Modelling with TensorFlow | ||
Version: 0.1.9 | ||
Date: 2017-05-28 | ||
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 = "[email protected]") | ||
Description: Existing tools for fitting bespoke statistical models (such as | ||
BUGS, JAGS and STAN) are very effective for moderately-sized problems, but | ||
don't scale so well to large datasets. These tools also require users to learn | ||
a domain-specific language and fix errors at compile time. greta enables users | ||
to construct probabilistic models interactively in native R code, then sample | ||
from those models efficiently using Hamiltonian Monte Carlo. TensorFlow is used | ||
to perform all of the calculations, so greta is particularly fast where the | ||
model contains large linear algebra operations. greta can also be run across | ||
distributed machines or on GPUs, just by installing the relevant version of | ||
TensorFlow. This package is in the early stages of development. Future releases | ||
will likely enable fitting models with fast approximate inference schemes, | ||
different samplers, and more distributions and operations. | ||
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 | ||
|
@@ -27,27 +16,29 @@ LazyData: true | |
Depends: | ||
R (>= 3.0) | ||
Collate: | ||
'greta_package.R' | ||
'package.R' | ||
'overloaded.R' | ||
'node_class.R' | ||
'node_types.R' | ||
'variable.R' | ||
'distributions.R' | ||
'probability_distributions.R' | ||
'unknowns_class.R' | ||
'greta_array_class.R' | ||
'as_data.R' | ||
'utils.R' | ||
'syntax.R' | ||
'distribution.R' | ||
'operators.R' | ||
'functions.R' | ||
'transformations.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, | ||
|
@@ -58,7 +49,8 @@ Suggests: | |
knitr, | ||
rmarkdown, | ||
DiagrammeR, | ||
MCMCvis, | ||
bayesplot, | ||
lattice, | ||
testthat, | ||
mvtnorm, | ||
MCMCpack, | ||
|
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