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sourceR (version 0.1.0)

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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Version

Install

install.packages('sourceR')

Monthly Downloads

35

Version

0.1.0

License

GPL-3

Maintainer

Poppy Miller

Last Published

April 21st, 2016

Functions in sourceR (0.1.0)

saBayes

Fits a non-parametric Bayesian model to source attribution data
summary.source_attribution

Summary function for saBayes output.
sim_SA_true

True values of the parameters used to generate the simulated data set sim_SA.
campy

Campylobacter source attribution data set from the Manawatu, New Zealand.
sim_SA

Simulated data
sourceR-package

Fits a non-parametric source attribution model