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Bayesian multivariate receptor modeling software: BNFA and bayesMRM

delete2021-04-01
delete8
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OA
AI
E
Eun Sug Park
E
Eun‐Kyung Lee
M
Man-Suk Oh *
DOI:10.1016/j.chemolab.2021.104280delete
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摘要

摘要

En 中文
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.
Keyword:
Multivariate receptor modeling
Bayesian factor analysis
Source apportionment
MATLAB
JAGS
Software
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期刊

Chemometrics and Intelligent Laboratory Systems 封面图
Chemometrics and Intelligent Laboratory Systems
IF:
3.8
论文数:
4.6K
被引数:
1.2W

机构

T
Texas A&M University System
学者数:
4.4W
论文数: 4.0W
被引数: 4.0K
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