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

PoisGammaDPUpdate function

Object of <code><a rd-options="" href="/link/R6Class?package=sourceR&version=1.0.0" data-mini-rdoc="sourceR::R6Class">R6Class</a></code> with methods for updating a <a rd-options="" href="/link/DirichletProcessNode?package=sourceR&version=1.0.0" data-mini-rdoc="sourceR::DirichletProcessNode">DirichletProcessNode</a> instance.

Format

Methods

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