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sourceR (version 1.0.0)

Fits a Non-Parametric Bayesian Source Attribution Model

Description

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.

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Install

install.packages('sourceR')

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Version

1.0.0

License

GPL-3

Maintainer

Poppy Miller

Last Published

January 15th, 2017

Functions in sourceR (1.0.0)

Human cases of campylobacteriosis and numbers of source samples positive for Campylobacter.

PoissonNode

sim_SA_prev

Simulated data prevalences.

sim_SA_data

Simulated data: Human cases of campylobacteriosis and numbers of source samples positive for Campylobacter.

DirichletProcessNode

Transformed Dirichlet node

sim_SA_true

True values for the parameters generating the simulated data.