{"65071":{"#nid":"65071","#data":{"type":"event","title":"Correlation Pursuit: forward stepwise variable selection for index models","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E Correlation Pursuit: forward stepwise variable selection for index \nmodels\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E\u0026nbsp; Michael Zhu\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn this talk, a stepwise procedure, correlation pursuit (COP), is \nproposed for variable selection under the sufficient dimension \nreduction framework. Unlike linear stepwise regression, COP does not \nimpose assumptions on the exact form of the relationship between the \nresponse variable and the predictor variables. The COP procedure \nselects variables that attain the maximum correlation between the \ntransformed response and the linear combination of the variables. Some \nasymptotic properties of the COP procedure are established, and in \nparticular, its variable selection performance under diverging sample \nsize and number of predictors has been investigated. The empirical \nperformance of the COP procedure in comparison with existing methods \nare demonstrated by both simulation studies and an real life example in \nfunctional genomics.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Correlation Pursuit: forward stepwise variable selection for index models"}],"uid":"27187","created_gmt":"2011-03-22 10:56:37","changed_gmt":"2016-10-08 01:54:34","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2011-03-31T13:00:00-04:00","event_time_end":"2011-03-31T14:00:00-04:00","event_time_end_last":"2011-03-31T14:00:00-04:00","gmt_time_start":"2011-03-31 17:00:00","gmt_time_end":"2011-03-31 18:00:00","gmt_time_end_last":"2011-03-31 18:00:00","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":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}