BayesMassBal: Bayesian Data Reconciliation of Separation Processes

Bayesian tools that can be used to reconcile, or mass balance, mass flow rate data collected from chemical or particulate separation processes aided by constraints governed by the conservation of mass. Functions included in the package aid the user in organizing and constraining data, using Markov chain Monte Carlo methods to obtain samples from Bayesian models, and in computation of the marginal likelihood of the data, given a particular model, for model selection. Marginal likelihood is approximated by methods in Chib S (1995) <doi:10.2307/2291521>.

Version: 1.0.0
Imports: Rdpack, Matrix, pracma, tmvtnorm, LaplacesDemon, HDInterval, coda
Suggests: knitr, rmarkdown, covr, spelling, tgp, testthat
Published: 2020-11-09
Author: Scott Koermer
Maintainer: Scott Koermer <skoermer at vt.edu>
BugReports: https://github.com/skoermer/BayesMassBal/issues
License: GPL-3
URL: https://github.com/skoermer/BayesMassBal
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: BayesMassBal results

Downloads:

Reference manual: BayesMassBal.pdf
Vignettes: Two_Node_Process
ssEst
Package source: BayesMassBal_1.0.0.tar.gz
Windows binaries: r-devel: BayesMassBal_1.0.0.zip, r-release: BayesMassBal_1.0.0.zip, r-oldrel: BayesMassBal_1.0.0.zip
macOS binaries: r-release: BayesMassBal_1.0.0.tgz, r-oldrel: BayesMassBal_1.0.0.tgz
Old sources: BayesMassBal archive

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