rubias: Bayesian Inference from the Conditional Genetic Stock Identification Model

Implements Bayesian inference for the conditional genetic stock identification model. It allows inference of mixed fisheries and also simulation of mixtures to predict accuracy. A full description of the underlying methods is available in a recently published article in the Canadian Journal of Fisheries and Aquatic Sciences: <doi.org/10.1139/cjfas-2018-0016>.

Version: 0.3.0
Depends: R (≥ 3.3.0)
Imports: dplyr, gtools, magrittr, Rcpp (≥ 0.12.5), readr, rlang, stringr, tibble, tidyr, RcppParallel
LinkingTo: Rcpp, RcppParallel
Suggests: knitr, rmarkdown, ggplot2
Published: 2019-06-10
Author: Eric C. Anderson [aut, cre], Ben Moran [aut]
Maintainer: Eric C. Anderson <eric.anderson at noaa.gov>
License: CC0
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: rubias citation info
Materials: README NEWS
CRAN checks: rubias results

Downloads:

Reference manual: rubias.pdf
Vignettes: Using the Fully Bayesian Model in rubias
An Overview of rubias Usage
An Explanation of the Underlying Data Structures in rubias
Package source: rubias_0.3.0.tar.gz
Windows binaries: r-devel: rubias_0.3.0.zip, r-release: rubias_0.3.0.zip, r-oldrel: rubias_0.3.0.zip
OS X binaries: r-release: rubias_0.3.0.tgz, r-oldrel: rubias_0.3.0.tgz
Old sources: rubias archive

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