Mathematical Sciences: Data Analysis, Modelling, and Inference

提出了以开发和测试新的基于模型的统计程序为中心的研究。包括在社会、生物医学和物理系统中的应用研究，这些研究的分析激发了某些新的模型和技术，这些模型和技术是为解决实际问题量身定做的。要研究的模型具有复杂的图形结构，相关的推论利用了几个统计和专家知识来源。统计技术包括计算密集的贝叶斯方法和信念函数方法，因此需要算法开发，并将通过评估数值实现来部分研究。

Studies are proposed which center around the development and testing of new model-based statistical procedures. Included are applied studies in social, biomedical and physical systems whose analysis motivates certain new models and techniques that are tailored to practical problem-solving. The models to be studied gnerally have complex graphical structures, and the related inferences draw on several sources of statistical and expert knowledge. The statistical techniques include Bayesian and belief function methods that are computationally intensive, thus requiring algorithm development and are to be studied in part through assessment of numerical implementations.