{"244901":{"#nid":"244901","#data":{"type":"event","title":"Statistics Seminar","body":[{"value":"\u003Cstrong\u003EGeorgia Tech Statistics Seminar Series\u003C\/strong\u003E\u003Cbr \/\u003E \u003Cbr \/\u003E Thursday, October 17, 2013 at 11:00 AM\u003Cbr \/\u003E Executive classroom, ISyE Main Building\u003Cbr \/\u003E \u003Cbr \/\u003E Inference and Experimental Planning for Lumen Degradation Data \u003Cbr \/\u003E Under A Wiener Diffusion Process\u003Cbr \/\u003E \u003Cbr \/\u003E \u003Cstrong\u003EDr. Yuhlong Lio\u003C\/strong\u003E\u003Cbr \/\u003E Professor\u003Cbr \/\u003E Department of Mathematical Sciences\u003Cbr \/\u003E University of South Dakota Vermillion, SD 57069\u003Cp\u003E\u003Cbr \/\u003E 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\u0027s 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.\u003Cbr \/\u003E \u003Cbr \/\u003E 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.\u0026nbsp; Dr. Lio is an Associate Editor for the Journal of Statistical Computation and Simulation.\u0026nbsp; His research interest includes Kernel smooth quantile estimation, reliability, survival analysis and statistical quality control.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Statistics Seminar"}],"uid":"27187","created_gmt":"2013-10-14 10:56:12","changed_gmt":"2016-10-08 02:05:11","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-10-17T12:00:00-04:00","event_time_end":"2013-10-17T13:00:00-04:00","event_time_end_last":"2013-10-17T13:00:00-04:00","gmt_time_start":"2013-10-17 16:00:00","gmt_time_end":"2013-10-17 17:00:00","gmt_time_end_last":"2013-10-17 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EHost: Dr. J.C. Lu (\u003Ca class=\u0022moz-txt-link-abbreviated\u0022 href=\u0022mailto:jclu@isye.gatech.edu\u0022\u003Ejclu@isye.gatech.edu\u003C\/a\u003E); please contact Dr. Lu for appointments.\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}