Statistics Seminar

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Event Details
  • Date/Time:
    • Thursday October 17, 2013 - Friday October 18, 2013
      11:00 am - 11:59 am
  • Location: ISyE Executive Classroom
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact

Host: Dr. J.C. Lu (jclu@isye.gatech.edu); please contact Dr. Lu for appointments.

Summaries

Summary Sentence: Statistics Seminar

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Georgia Tech Statistics Seminar Series

Thursday, October 17, 2013 at 11:00 AM
Executive classroom, ISyE Main Building

Inference and Experimental Planning for Lumen Degradation Data
Under A Wiener Diffusion Process

Dr. Yuhlong Lio
Professor
Department of Mathematical Sciences
University of South Dakota Vermillion, SD 57069


Abstract: This seminar presents investigations of the lumen degradation of light emitting diodes (LEDs) subject to stress loadings. Cumulative damage measurements are collected from a two-variable constant-stress accelerated degradation test (ADT). The underlying process for the data is a Wiener diffusion process with a drift which depends on the stress loadings. General statistical inferences on the parameters and percentiles of the LED lifetime distribution are presented. Approximate lower confidence bounds of the LED percentile lifetime are given using the Fisher information of the maximum-likelihood estimates and Bonferroni's inequality. This work establishes optimal strategies on the constant-stress ADT plan for a compromised decision between experiment budget and estimation precision. The study provides an algorithm to search the optimal strategy for the ADT. Finally, an example of LED tests is used to illustrate applications of the proposed methods.

Bio: Dr. Yuhlong Lio received Ph.D. in Statistics from University of South Carolina in 1987. Since then he has served as assistant professor, associate professor and professor in the Department of Mathematical Sciences, University of South Dakota.  Dr. Lio is an Associate Editor for the Journal of Statistical Computation and Simulation.  His research interest includes Kernel smooth quantile estimation, reliability, survival analysis and statistical quality control.

Additional Information

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School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Oct 14, 2013 - 6:56am
  • Last Updated: Oct 7, 2016 - 10:05pm