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자연과학대학
통계학전공
Journal papers
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Bayesian multivariate receptor modeling software: BNFA and bayesMRM
Title
Bayesian multivariate receptor modeling software: BNFA and bayesMRM
Authors
Park E.S.
;
Lee E.-K.
;
Oh M.-S.
Ewha Authors
오만숙
;
이은경
SCOPUS Author ID
오만숙
; 이은경
Issue Date
2021
Journal Title
Chemometrics and Intelligent Laboratory Systems
ISSN
0169-7439
Citation
Chemometrics and Intelligent Laboratory Systems vol. 211
Keywords
Bayesian factor analysis
;
JAGS
;
MATLAB
;
Multivariate receptor modeling
;
R
;
Software
;
Source apportionment
Publisher
Elsevier B.V.
Indexed
SCIE; SCOPUS
Document Type
Article
Abstract
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. © 2021 The Author(s)
DOI
10.1016/j.chemolab.2021.104280
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