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TZID:America/New_York
X-LIC-LOCATION:America/New_York
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DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
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DTSTART:20250309T020000
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DESCRIPTION:NOTE: BIS 525 students are required to attend in person. Other
 s are invited to attend in person\, but may also attend via Zoom. SPEAKER
  : Ali Shojaie\, PhD\, Professor of Biostatistics\, Adjunct Professor of 
 Statistics\, University of Washington TITLE : "Estimation and Inference f
 or Networks of Multi-Experiment Point Processes" ABSTRACT: Modern high-di
 mensional point process data\, especially those from neuroscience experim
 ents\, often involve observations from multiple conditions and/or experim
 ents. Networks of interactions corresponding to these conditions are expe
 cted to share many edges\, but also exhibit unique\, condition-specific o
 nes. However\, the degree of similarity among the networks from different
  conditions is generally unknown. To address these needs\, we propose a j
 oint estimation procedure for networks of high-dimensional point processe
 s that incorporates easy-to-compute weights in order to data-adaptively e
 ncourage similarity between the estimated networks. We also propose a pow
 erful hierarchical multiple testing procedure for edges of all estimated 
 networks\, which accounts for the data-driven similarity structure of the
  multi-experiment networks. Compared to conventional multiple testing pro
 cedures\, our proposed procedure greatly reduces the number of tests and 
 results in improved power\, while tightly controlling the family-wise err
 or rate. Unlike existing procedures\, our method is also free of assumpti
 ons on dependency between tests\, offers flexibility on p-values calculat
 ed along the hierarchy\, and is robust to misspecification of the hierarc
 hical structure.\n\nSpeaker:\nAli Shojaie\, PhD\n\nAdmission:\nFree\n\nDe
 tails URL:\nhttps://medicine.yale.edu/event/ysph-biostatistics-seminar-tb
 a-10-4/\n
DTEND;TZID=America/New_York:20221004T130000
DTSTAMP:20261022T083132Z
DTSTART;TZID=America/New_York:20221004T120000
GEO:41.302961;-72.931638
LOCATION:106-A&B\, 47 College Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar: “Estimation and Inference for Networks
  of Multi-Experiment Point Processes”
UID:4b7e0c77-e6cb-4fbf-b77b-fbccb16e16b8
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