Rainier

Rainier

  • Docs
  • GitHub

›Installation

Overview

  • Introduction to Rainier
  • Priors and Random Variables
  • Likelihoods and Observations
  • Vectors and Variables
  • Posteriors and Predictions

Installation

  • Getting Rainier
  • Using Jupyter
  • Roadmap
  • Modules

API Reference

  • Distributions
  • Model and Trace
  • Generator
  • Real
  • Vec
  • Samplers

Implementation

  • Bryant (2020)

Rainier's Modules

The diagram below illustrates Rainier's published modules, the dependencies between them, and a representative type for each. It also shows dependencies on external packages.

The modules were designed to be as standalone as possible, so that you can, for example:

  • use the sampler implementations without Rainier's compute graph or model API
  • build something entirely different on top of the compute graph
  • build an alternative modeling API that still makes use of the compute graph and samplers
  • use the notebook utilities in a completely different project

modules.svg

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