Modeling and Estimation for Electronics and Semiconductor Products

这项提案支持四名学生(两名由国家科学基金会和两名工业赞助商)将研究生研究与对工业问题的实际贡献相结合。主要的工业合作伙伴是北电，但我们在半导体研究公司、德克萨斯仪器公司和北卡罗来纳州立大学先进电子材料处理中心的同事也将提供专业知识和实验室准入。因此，该项目将在统计学和工程学之间搭建一座桥梁，无论是在校园内外，还是在进行跨学科研究方面。学生将在以下方面获得经验：阐述研究问题、确定统计和工程贡献、探索潜在的基础统计研究领域，以及向不同学科的科学家进行口头和书面陈述。在这一建议中，以下新的研究将有助于工业应用和学术基础研究：(1)分析时间或空间相关的非正态离散或连续数据的灵活建模和估计方法；(2)双边时间序列模型的稳健估计方法；(3)时间相关重复测量的非线性随机系数模型的稳健估计方法。所提出的统计程序的性质将通过有限样本模拟和应用于北电的真实例子的渐近理论来评估。该项目的经验将作为我们与研究三角公园和罗利公司重组关系的典范。学生们将每周花10到20个小时在工业现场、工程实验室和统计部门进行研究。受训者及其导师将在适当的会议上介绍他们的工作，并在统计和工程期刊上发表与项目有关的研究成果。该项目由公安部多学科活动办公室S和数学科学部共同支持。

This proposal supports four students (two by NSF and two by industrial sponsors) to integrate graduate research with practical contributions to industrial problems. The main industrial partner is Nortel, but our colleagues in the Semiconductor Research Corporation, Texas Instruments, and the Center for Advanced Electronic Materials Processing at North Carolina State University will also provide expertise and laboratory access. Thus, this program will build a bridge between statistics and engineering, both on and off campus, for conducting interdisciplinary research. The students will gain experience in formulating research problems, in identifying statistical and engineering contributions, in exploring potential basic statistical research areas, and in presenting (oral and written) to scientists from different disciplines. In this proposal, the following new research will benefit both industrial applications and academic basic research: (1) a flexible modeling and estimation method for analyzing temporally or spatially correlated non-normal discrete or continuous data, (2) a robust estimation method in bilateral time series model, and (3) a robust estimation procedure in nonlinear random coefficient model for temporally correlated repeated measurements. The properties of the proposed statistical procedures will be evaluated through finite sample simulation and asymptotic theory applied to real-life examples from Nortel. The experience from this program will serve as a model to restructure our relationships with companies at Research Triangle Park and Raleigh. The students will spend 10 to 20 hours per week conducting research at industrial sites, engineering laboratories and the statistics department. The trainees and their mentors will present their work at appropriate conferences and publish research relevant to projects in statistical and engineering journals. This GOALI project is jointly supported by the MPS Office of Multidisciplinary Activitie s (OMA) and the Division of Mathematical Sciences (DMS).