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UID:20260202T004106EST-7134Av8eSz@132.216.98.100
DTSTAMP:20260202T054106Z
DESCRIPTION:Title: Survival analysis of extreme events with missing observa
 tions.\n\nAbstract:\n\nThe analysis of extreme wave surge heights in Atlan
 tic Canada is key in determining areas that are subject to flooding or at 
 risk of severe damage from intense storms. One method for modelling extrem
 e events is through the block maxima approach which divides a series of ob
 servations into equal-sized blocks to extract the maxima after which infer
 ence is conducted on the generalized extreme value (GEV) distribution. Whe
 n observations at the series level are missing\, the observed block maxima
  may not correspond to the true block maxima. In this presentation\, we in
 troduce this missing data problem in the context of an extreme value analy
 sis and explain how concepts from survival analysis can be used to improve
  inferences on the GEV distribution using the observed block maxima.\n\nSp
 eaker\n\nJames McVittie is an Assistant Professor in the Department of Mat
 hematics and Statistics at the University of Regina. He completed his Mast
 er’s and PhD degrees in Mathematics and Statistics at ºÚÁÏÍø±¬³Ô¹Ï un
 der the supervision of Professors David A. Stephens and David B. Wolfson\,
  in July 2017 and October 2021\, respectively. His research interests incl
 ude survival analysis\, missing data problems\, combined cohort methodolog
 ies\, and biostatistics.\n
DTSTART:20260123T203000Z
DTEND:20260123T213000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:James McVittie (University of Regina)
URL:/mathstat/channels/event/james-mcvittie-university
 -regina-370258
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