B2Z: An R Package for Bayesian Two-Zone Models
B2Z: An R Package for Bayesian Two-Zone Models
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B2Z：贝叶斯两区模型的 R 包
DOI：
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发表时间：
2011
期刊：
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通讯作者：
G. Ramachandran
中科院分区：
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作者：
João V. D. Monteiro;Sudipto Banerjee;G. Ramachandran
工业卫生的一个主要问题是估计工人接触化学、物理和生物制剂的情况。数学模型越来越多地被用作评估职业暴露的方法。然而，由于缺乏对接触决定因素的定量知识，在真实的环境中预测接触受到限制。最近，Zhang、Banerjee、Yang、Lungu和Ramachandran（2009年）提出了贝叶斯分层模型，用于估计两区微分方程模型的参数和暴露浓度，以及预测污染源附近和远离污染源的区域的浓度。但是，贝叶斯估计通常需要大量的用户定义代码和调优。在本文中，我们介绍了一个统计软件包，B2Z，建立在R统计计算平台，实现了贝叶斯模型估计模型参数和暴露浓度的两个区域模型。我们讨论我们的包背后的算法，并说明其使用模拟和真实的数据的例子。
A primary issue in industrial hygiene is the estimation of a worker's exposure to chemical, physical and biological agents. Mathematical modeling is increasingly being used as a method for assessing occupational exposures. However, predicting exposure in real settings is constrained by lack of quantitative knowledge of exposure determinants. Recently, Zhang, Banerjee, Yang, Lungu, and Ramachandran (2009) proposed Bayesian hierarchical models for estimating parameters and exposure concentrations for the two-zone differential equation models and for predicting concentrations in a zone near and far away from the source of contamination. Bayesian estimation, however, can often require substantial amounts of user-defined code and tuning. In this paper, we introduce a statistical software package, B2Z, built upon the R statistical computing platform that implements a Bayesian model for estimating model parameters and exposure concentrations in two-zone models. We discuss the algorithms behind our package and illustrate its use with simulated and real data examples.