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.

拟议研究的一个重要目标是开发基因定位方法，即，在人类或实验生物体中鉴定含有影响感兴趣性状的基因的基因组区域。在噪声背景中搜索一个或多个信号的位置的参数集出现在基因作图中，其中信号指示基因的存在。类似的问题也出现在脑图谱、天文学和生物信息学中。他们解决方案的一个重要部分涉及随机场超过高阈值的概率。一个统一的分析方法和顺序蒙特卡罗方法将开发这些边界交叉概率进行评估。其他方法的创新，拟议的研究是新的动态经验贝叶斯模型和方法，顺序监督程序，和自适应控制方案的输入输出系统，可能会偶尔突然的结构变化。 发展中的动态经验贝叶斯方法已应用于保险费率制定、经济学中的动态面板数据、生物医学研究中的纵向数据和风险管理。在最近的金融危机和石油泄漏灾难之后，顺序监测和适应性风险控制具有及时的相关性。序贯蒙特卡罗方法在通信网络和风险管理中的非线性滤波和稀有事件模拟方面有重要的应用。基因定位为人类疾病研究以及农业和畜牧业提供了重要工具。拟议研究的更广泛影响包括：（i）遗传学，工程，金融，保险，风险管理和监督的直接影响，以及（ii）通过开发新的高级课程并让研究生参与研究的所有阶段，在学术界，工业界和政府中培训下一代科学家。