This is a flexible Bayesian mixture model package written in
the probabilistic programming language Stan (https://mc-stan.org/) for R
(https://www.r-project.org/). It estimates source mixing proportions by
incorporating simultaneous likelihood evaluation from two independent data
streams collected from the mixture of interest: one obtained from chemical
tracers/biomarkers (i.e., a single tracer measurement per observation, e.g.,
from stable isotopes and fatty acids), and another yielding source
composition (e.g., based on eDNA). MixMustR also allows for the estimation
of an additional, unsampled source component to partially relax the
assumption that the mixing proportions from all samples sources should sum
up to 1. MixMustR should have wide applicability in ecological studies,
particularly given the growing usage and availability of multiple tracers
spanning traditional stable isotopes and eDNA to understand carbon
source-sink dynamics, and a mixture of stables isotope, fatty acids and eDNA
to unravel trophic interactions.
Useful links: