Statistical Methodology and Applications to Economics, Engineering and Genetics

统计方法及其在经济学、工程和遗传学中的应用

• 批准号: 1106535
• 负责人: Tze Lai
• 金额: $ 39.99万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1106535&HistoricalAwards=false
• 关键词: Statistical; Methodology; Applications; Economics; Engineering

An important objective of the proposed research is to develop methods for gene mapping, i.e., the identification of genomic regions containing a gene (or genes) affecting a trait of interest in either humans or in experimental organisms. Searching a parameter set for the location of one or more signals in a noisy background arise in gene mapping where the signals indicate the presence of a gene. Similar problems arise in brain mapping, astronomy, and bioinformatics. An important part of their solution involves the probability that a random field exceeds a high threshold. A unified analytic approach and sequential Monte Carlo methods will be developed to evaluate these boundary crossing probabilities. Other methodological innovations of the proposed research are new dynamic empirical Bayes models and methods, sequential surveillance procedures, and adaptive control schemes for input-output systems that may undergo occasional abrupt structural changes. The dynamic empirical Bayes approach under development has applications to insurance rate-making, dynamic panel data in economics, longitudinal data in biomedical studies, and risk management. Sequential surveillance and adaptive risk control are of timely relevance in the aftermath of the recent financial crisis and oil spill disaster. Sequential Monte Carlo methods have important applications to nonlinear filtering and to rare event simulation in communication networks and risk management. Gene mapping provides an important tool in the study of human diseases, and in agriculture and animal husbandry. The broader implications of the proposed research include (i) direct implications in genetics, engineering, finance, insurance, risk management and surveillance, and (ii) training of the next generation of scientists in academia, industry, and government by developing new advanced courses and involving graduate students in all phases of the research.

拟议的研究的一个重要目标是开发基因映射的方法，即鉴定包含一个基因（或基因）的基因组区域，影响人类或实验生物中感兴趣的特征。搜索一个参数集以在嘈杂背景中的一个或多个信号的位置出现在基因映射中，其中信号表示基因的存在。大脑映射，天文学和生物信息学也出现了类似的问题。他们的解决方案的重要部分涉及随机场超过高阈值的概率。将开发一种统一的分析方法和顺序的蒙特卡洛方法来评估这些边界跨越概率。拟议研究的其他方法论创新是新的动态经验贝叶斯模型和方法，顺序监视程序以及用于输入输出系统的自适应控制方案，这些系统可能会偶尔发生突然的结构变化。 开发中的动态经验贝叶斯方法在保险费率，经济学中的动态面板数据，生物医学研究中的纵向数据以及风险管理中有应用。在最近的金融危机和溢油灾难之后，顺序监视和适应性风险控制与及时相关。顺序的蒙特卡洛方法在通信网络和风险管理中对非线性过滤以及罕见的事件模拟具有重要的应用。基因映射在研究人类疾病以及农业和畜牧业中提供了重要的工具。拟议研究的广泛含义包括（i）对遗传学，工程，金融，保险，风险管理和监视的直接影响，以及（ii）通过开发新的高级课程并参与研究阶段的研究生，培训学术界，工业和政府的下一代科学家。