Package: sgmcmc
Type: Package
Title: Stochastic Gradient Markov Chain Monte Carlo
Version: 0.1.0
Authors@R: c(
    person("Jack", "Baker", email = "j.baker1@lancaster.ac.uk", role = c("aut", "cre", "cph")),
    person( "Christopher", "Nemeth", role = c("aut", "cph") ), 
    person( "Paul", "Fearnhead", role = c( "aut", "cph" ) ),
    person( "Emily B.", "Fox", role = c("aut", "cph") ), 
    person( "STOR-i", role = c( "cph" ) ))
Description: Provides functions that performs popular stochastic gradient Markov chain Monte Carlo 
  (SGMCMC) methods on user specified models. The required gradients are automatically calculated 
  using 'TensorFlow' <https://www.tensorflow.org/>, an efficient library for numerical computation.
  This means only the log likelihood and log prior functions need to be specified. 
  The methods implemented include stochastic gradient Langevin dynamics (SGLD), stochastic gradient
  Hamiltonian Monte Carlo (SGHMC), stochastic gradient Nose-Hoover thermostat (SGNHT) and 
  their respective control variate versions for increased efficiency.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0), tensorflow
SystemRequirements: TensorFlow (https://www.tensorflow.org/)
Suggests: testthat, MASS, knitr, ggplot2, rmarkdown
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
URL: https://github.com/STOR-i/sgmcmc
BugReports: https://github.com/STOR-i/sgmcmc/issues
NeedsCompilation: no
Packaged: 2017-07-18 19:07:06 UTC; jbaker
Author: Jack Baker [aut, cre, cph],
  Christopher Nemeth [aut, cph],
  Paul Fearnhead [aut, cph],
  Emily B. Fox [aut, cph],
  STOR-i [cph]
Maintainer: Jack Baker <j.baker1@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2017-07-18 21:55:24 UTC
