Bayesian Mixing Models in R R package MixSIAR version 3.1.12 Creates and runs Bayesian mixing models to analyze biological tracer data (i.e. stable isotopes, fatty acids), which estimate the proportions of source (prey) contributions to a mixture (consumer). 'MixSIAR' is not one model, but a framework that allows a user to create a mixing model based on their data structure and research questions, via options for fixed/ random effects, source data types, priors, and error terms. 'MixSIAR' incorporates several years of advances since 'MixSIR' and 'SIAR'. Software Depends: R (>= 3.6.0) Imports: ggplot2 (>= 3.3.0), R2jags (>= 0.5-7), MASS (>= 7.3), RColorBrewer (>= 1.1), reshape (>= 0.8.7), reshape2 (>= 1.4.3), lattice (>= 0.20-35), MCMCpack (>= 1.4-2), ggmcmc (>= 1.1), coda (>= 0.19-1), loo (>= 2.0.0), bayesplot (>= 1.4.0), splancs (>= 2.01-40) Suggests: knitr, rmarkdown, testthat Brian Stock <bstock09@gmail.com> Comprehensive R Archive Network (CRAN) Brian Stock [cre, aut], Brice Semmens [aut], Eric Ward [ctb], Andrew Parnell [ctb], Andrew Jackson [ctb], Donald Phillips [ctb] GPL-3 2020-10-20 application/tgz https://CRAN.R-project.org/package=MixSIAR doi:10.32614/CRAN.package.MixSIAR