DirichletProcessNode


Uses transformation due to Betancourt 2013
https://arxiv.org/pdf/1010.3436v4.pdf


node

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

DirichletProcessNode 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 constructing a DAG.

Format

Methods

Object of <code><a rd-options='' href='R6Class'>R6Class</a></code> with methods for constructing a DAG.

DirichletProcessNode: Transformed Dirichlet node

Description

Usage

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Value

Format

Methods

Details