runjags: An R Package Providing Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS
runjags: An R Package Providing Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS
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DOI：
10.18637/jss.v071.i09
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发表时间：
2016-07-01
影响因子：
5.8
通讯作者：
Denwood, Matthew J.
中科院分区：
文献类型：
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作者：
Denwood, Matthew J.
RunJags包提供了一组接口函数，以便于从R内部在JAG中运行马尔科夫链蒙特卡罗模型。它提供了适当收敛和样本长度诊断的自动计算、对常用图形输出和汇总统计数据的用户友好访问，以及运行JAG的并行方法。模板模型规范可以使用标准的lme4风格的公式界面来生成，以帮助不太熟悉Bugs语法的用户。使用高性能计算集群，例如由并行提供的集群，实现了自动化模拟研究功能，以促进模型性能评估以及Drop-k类型交叉验证研究。对于JAG的模块扩展也包含在runjgs中，提供了Pareto分布族和一系列信息最少的先验，包括DuMouchel和Half-Cauchy先验。本文概述了该程序包的主要功能，并给出了评估两种等价模型公式对不同先验分布的敏感性的模拟研究的说明。
The runjags package provides a set of interface functions to facilitate running Markov chain Monte Carlo models in JAGS from within R. Automated calculation of appropriate convergence and sample length diagnostics, user-friendly access to commonly used graphical outputs and summary statistics, and parallelized methods of running JAGS are provided. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. Automated simulation study functions are implemented to facilitate model performance assessment, as well as drop-k type cross-validation studies, using high performance computing clusters such as those provided by parallel. A module extension for JAGS is also included within runjags, providing the Pareto family of distributions and a series of minimally-informative priors including the DuMouchel and half-Cauchy priors. This paper outlines the primary functions of this package, and gives an illustration of a simulation study to assess the sensitivity of two equivalent model formulations to different prior distributions.