{"49710":{"#nid":"49710","#data":{"type":"event","title":"Analysis of Large-Scale Computer Experiments","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE: \u003C\/strong\u003EAnalysis of Large-Scale Computer Experiments\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E Lulu Kang\n\u003Cbr \/\u003EPhD Candidate\u0026nbsp; (in the Statistics Program)\n\u003Cbr \/\u003ESchool of Industrial and Systems Engineering\n\u003Cbr \/\u003EGeorgia Tech\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EComputer experiments simulate the engineering systems by \nimplementing the mathematical models governing the systems in computers. \nRecently, experiments having large number of input variables and \nexperimental runs started to emerge. In the existing literature, kriging \nhas been commonly used for approximating the complex computer models, \nbut it has limitations for dealing with the large-scale experiments due \nto its computational complexity and numerical stability. In this work, I \npropose a new modeling approach known as regression-based inverse \ndistance weighting (RIDW). The new predictor is shown to be \ncomputationally more efficient than kriging while producing comparable \nprediction performance. We also develop a heuristic method for \nconstructing confidence intervals for prediction. I will also discuss \nextensions of RIDW and my future research directions on this exciting topic\n\u003Cbr \/\u003E\nBio:\n\u003Cbr \/\u003ELulu Kang is a Ph.D. candidate in the Statistics Program of the School \nof Industrial and Systems Engineering at Georgia Institute of \nTechnology. She is working with Professor Roshan J. Vengazhiyil. Her \nresearch interests are in developing statistical theories and \nmethodologies, as well as their applications in physical science and \nengineering.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"Analysis of Large-Scale Computer Experiments","format":"limited_html"}],"field_summary_sentence":[{"value":"Analysis of Large-Scale Computer Experiments"}],"uid":"27187","created_gmt":"2010-01-26 08:10:24","changed_gmt":"2016-10-08 01:49:32","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-01-28T10:00:00-05:00","event_time_end":"2010-01-28T11:00:00-05:00","event_time_end_last":"2010-01-28T11:00:00-05:00","gmt_time_start":"2010-01-28 15:00:00","gmt_time_end":"2010-01-28 16:00:00","gmt_time_end_last":"2010-01-28 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"7919","name":"Experiments"}],"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}