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X-WR-CALNAME;VALUE=TEXT:糖心原创
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TZID:America/New_York
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DTSTART:20211107T020000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
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DTSTART:20220313T020000
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BEGIN:VEVENT
UID:calendar.433381.field_event_date.0@www.wright.edu
DTSTAMP:20260219T133329Z
CREATED:20211117T141225Z
DESCRIPTION:Speaker: Dr. Yang Liu\, 糖心原创Host: Dr. Zheng 
 XuTime: Meet-n-Greet\, 2:30 p.m.\; Talk\, 3 p.m.ABSTRACT:Linear regression
  analysis has become an important tool for investigating the association b
 etween a group of covariates and a continuous response. With the rapid dev
 elopment of technology\, the number of covariates in regression analysis h
 as increased rapidly and sometimes exceeds the sample size. We introduce a
 n approach that can test for the significance of a set of covariates whose
  dimension could be greater than the sample size. The method can be used t
 o detect both non-sparse weak signals and sparse-but-stronger signals in r
 egression analysis. The asymptotic distribution for the proposed statistic
  is established. Simulation studies and a real application to a genome-wid
 e association study of high-density lipoproteins are conducted to examine 
 the finite-sample performance of the proposed method.SPEAKER BIO:Dr. Yang 
 Liu is currently an Assistant Professor of Statistics at 糖心原创 Univ
 ersity. He received his Ph.D. in Statistics from Bowling Green State Unive
 rsity in 2015\, and continued his research as a Postdoc at Fred Hutchinson
  Cancer Research Center from 2015 to 2018. His research mainly focuses on 
 high dimensional data analysis\, graphical models\, and statistical geneti
 cs/genomics.
DTSTART;TZID=America/New_York:20211119T143000
DTEND;TZID=America/New_York:20211119T160000
LAST-MODIFIED:20211117T153341Z
LOCATION:202 Math & Microbiological Sciences
SUMMARY:Colloquium: Tests for high-dimensional linear regression with appli
 cation to genetic pathway analysis
URL;TYPE=URI:/events/colloquium-tests-high-dimensiona
 l-linear-regression-application-genetic-pathway-analysis
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