PoisGammaDPUpdate

This class implements a marginal Gibbs sampler for a Dirichlet process
prior on the mean of a Poisson distributed random variable, with a Gamma-distributed
base function.

node

Dirichlet-process

Implements a non-parametric source attribution model to attribute
cases of disease to sources in Bayesian framework with source and type effects.
Type effects are clustered using a Dirichlet Process. Multiple times and
locations are supported.

Poppy Miller

sourceR

Fits a Non-Parametric Bayesian Source Attribution Model

Chris Jewell

Jonathan Marshall

Nigel French

PoisGammaDPUpdate function

Object of <code><a rd-options="" href="/link/R6Class?package=sourceR&version=1.0.1" data-mini-rdoc="sourceR::R6Class">R6Class</a></code> with methods for updating a <a rd-options="" href="/link/DirichletProcessNode?package=sourceR&version=1.0.1" data-mini-rdoc="sourceR::DirichletProcessNode">DirichletProcessNode</a> instance.

Format

<p></p><p><dl class="dl-horizontal">
  <dt><code>new(node)</code></dt><dd>constructor takes an instance of a <a rd-options="" href="/link/DirichletProcessNode?package=sourceR&version=1.0.1" data-mini-rdoc="sourceR::DirichletProcessNode">DirichletProcessNode</a> <code>node</code></dd>
  <dt><code>update()</code></dt><dd>when called, updates <code>node</code></dd>
</dl></p>

Methods

PoisGammaDPUpdate — PoisGammaDPUpdate

Object of <code><a rd-options='' href='R6Class'>R6Class</a></code> with methods for updating a <a rd-options='' href='DirichletProcessNode'>DirichletProcessNode</a> instance.

PoisGammaDPUpdate: PoisGammaDPUpdate

Description

Usage

Arguments

Value

Format

Methods

Details