sourceR: Fits a Non-Parametric Bayesian Source Attribution Model

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.

Version: 1.1.0
Depends: R (≥ 3.4.0), dplyr, tensorA, assertthat
Imports: methods, Rcpp (≥ 1.0.4), gtools, R6, cluster, stats, gplots, SPIn, grDevices, reshape2
LinkingTo: Rcpp
Suggests: testthat, R.rsp
Published: 2020-08-31
Author: Poppy Miller [aut, cre, cph], Chris Jewell [aut], Jonathan Marshall [ctb], Nigel French [ctb]
Maintainer: Poppy Miller <p.miller at lancaster.ac.uk>
License: GPL-3
NeedsCompilation: yes
CRAN checks: sourceR results

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Reference manual: sourceR.pdf
Vignettes: Using sourceR
Package source: sourceR_1.1.0.tar.gz
Windows binaries: r-devel: sourceR_1.1.0.zip, r-release: sourceR_1.1.0.zip, r-oldrel: sourceR_1.1.0.zip
macOS binaries: r-release: sourceR_1.1.0.tgz, r-oldrel: sourceR_1.1.0.tgz
Old sources: sourceR archive

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