Bayesian multivariate receptor modeling software: BNFA and bayesMRM

We present user-friendly software tools to implement Bayesian multivariate receptor modeling in the form of a MATLAB function (BNFA) and an R package (bayesMRM). A basic model and a Markov chain Monte Carlo algorithm underlying BNFA and bayesMRM are given. An example of implementation based on real air pollution data is also provided. Users can freely choose between BNFA and bayesMRM depending on their computing platform. These tools are expected to facilitate implementation of Bayesian multivariate receptor models and/or Bayesian nonnegative factor analysis models and promote their use in chemometrics. ●We developed two user-friendly software tools, BNFA (as a MATLAB toolbox) and bayesMRM (as an R package), to implement Bayesian multivariate receptor modeling.●Both tools are freely available to users, and users can choose between BNFA and bayesMRM depending on their computing platform.●The software requires little knowledge on MCMC and frees users from advanced coding for implementation.●BNFA and bayesMRM also provide useful plots and tables for summarizing and visualizing the results of Bayesian estimation.●These tools are expected to promote the use of Bayesian multivariate receptor modeling and Bayesian factor analysis in chemometrics.