greta-structures

zeros

ones

These structures can be used to set up more complex models. For
  example, scalar parameters can be embedded in a greta array by first creating a
  greta array with <code>zeros()</code> or <code>ones()</code>, and then embedding the
  parameter value using greta&#39;s replacement syntax

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.

greta-structures: greta Data Structures

Description

Usage

Arguments

Value

Examples