greta-model

print.greta_model

plot.greta_model

further arguments passed to or from other methods (currently ignored).

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Methods to inspect <code>greta_model</code> objects (returned by
  <code><a rd-options="" href="/link/define_model?package=greta&version=0.1.7" data-mini-rdoc="greta::define_model">define_model</a></code>), including a graphic representation of the
  constructed model.

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.

Nick Golding

greta

Probabilistic Modelling with TensorFlow

greta-model function

Methods to inspect <code>greta_model</code> objects (returned by
  <code><a rd-options='' href='define_model'>define_model</a></code>), including a graphic representation of the
  constructed model.

greta-model: Greta Model Objects

Description

Usage

Arguments

Details