Bayesian Analysis, Computation and Communication

贝叶斯统计方法被应用于经济、法律、医学、心理学和气象学等不同领域中信息有限的决策情况。贝叶斯分析、计算和通信(BACC)项目的目标是为更广泛的社会科学社区提供快速、方便地使用最先进的模拟方法进行贝叶斯分析、计算和通信的途径。为了实现其目标，该项目将开发结合数理统计和计算机科学最新创新的软件。BACC软件的一个独特而重要的特征是，它将其工具作为流行的数学应用程序MatLab、Gauss、S+和R的扩展来实现。使这一特征成为可能的体系结构在贝叶斯软件领域是独一无二的，结合了核心代码、模型特定代码、应用代码和专门的数学例程库。该项目将扩展提供给用户的模型套件，为用户开发新模型提供一组高级命令，并结合结构化程序来交叉检查算法的有效性。它还将强调向社会科学研究界推广和传播该软件，并将其纳入研究生和博士后教育。

Bayesian statistical methods are applied in situations of decision making with limited information in diverse fields including economics, law, medicine, psychology, and meteorology. The objective of the Bayesian Analysis, Computation and Communication (BACC) project is to provide the wider social science community with rapid, convenient access to state-of-the-art simulation methods for Bayesian analysis, computation and communication. To meet its objectives, the project will develop software incorporating recent innovations in mathematical statistics and computer science. A unique and important feature of the BACC software is that it implements its tools as extensions to the popular mathematical applications programs Matlab, Gauss, S-plus, and R. The architecture that makes this feature possible is unique within the domain of Bayesian software, combining core code, model-specific code, application code, and a specialized mathematical routine library.This project will expand the suite of models provided to users, provide a set of high-level commands for users developing new models, and incorporate structured procedures to cross-check the validity of algorithms. It also will emphasize outreach and dissemination of the software to the social science research community and its incorporation in graduate and postdoctoral education.