Mathematical Sciences: Methodological and Computational Aspects of Statistical Modeling and Inference

数学科学：统计建模和推理的方法论和计算方面

• 批准号: 8807085
• 负责人: Arthur Dempster
• 金额: $ 12.02万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-07-01 至 1991-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8807085&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Methodological; Computational; Aspects

This work will focus on three areas of theoretical statistics: (1) Bayesian modelling and analysis of time series, including time domain and frequency domain approaches to both long memory and short memory models, (2) other Bayesian projects including nonlinear regression models and measurement error models, and (3) Bayes causal networks and belief functions, including mathematical characterization of these new models, as well as the development of principles for model construction and computation that are required for practical use. Dempster's work in theoretical statistics is becoming foundational for other scientists attempting to incorporate the realities of uncertainty into expert computer systems. In addition to extending relevant theory, he will tackle the computational bottleneck that now blocks successful widespread implementation of these models.

这项工作将重点关注理论统计的三个领域：（1）时间序列的贝叶斯建模和分析，包括时间域和频域的方法，用于长期记忆和短记忆模型，（2）其他贝叶斯项目，包括非线性回归模型和测量误差模型，以及（3）贝叶斯的因果网络和信仰模型，包括用于这些开发的数学构建，以及这些开发的数学构建，以及这些开发以及这些新型的特征，以及以及这些新型的特征。 Dempster在理论统计中的工作正成为其他科学家试图将不确定性现实纳入专家计算机系统的基础。 除了扩展相关理论外，他还将解决现在可以阻止这些模型成功实现的计算瓶颈。