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).
