BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal iCal API//EN X-WR-CALNAME:Events items teaser X-WR-TIMEZONE:America/Toronto BEGIN:VTIMEZONE TZID:America/Toronto X-LIC-LOCATION:America/Toronto BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20201101T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:6827bccaa2aaa DTSTART;TZID=America/Toronto:20211104T160000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20211104T170000 URL:/statistics-and-actuarial-science/events/david-spro tt-distinguished-lecture-christian-genest SUMMARY:David Sprott Distinguished Lecture by Christian Genest CLASS:PUBLIC DESCRIPTION:Summary \n\nPlease Note: This seminar will be given online.\n\ nDistinguished Lecture Series\n\nCHRISTIAN GENEST\, Canada Research Chair in Stochastic Dependence\nModeling\, Professor\n_McGill University_\n\nBAY ESIAN HIERARCHICAL MODELING OF SPATIAL EXTREMES\n\n----------------------- --\n\nClimate change and global warming have increased the need to assess\ nand forecast environmental risk over large domains and to develop\nmodels for the extremes of natural phenomena such as droughts\,\nfloods\, torre ntial precipitation\, and heat waves. Because\ncatastrophic events are rar e and evidence is limited\, Bayesian methods\nare well suited for the area l analysis of their frequency and size. In\nthis talk\, a multi-site model ing strategy for extremes will be\ndescribed in which spatial dependence i s captured through a latent\nGaussian random field whose behavior is driv en by synthetic\ncovariates from climate reconstruction models. It will be seen through\ntwo vignettes that the site-to-site information sharing mec hanism\nbuilt into this approach does not only generally improve inference at\nany location but also allows for smooth interpolation over large\,\ns parse domains.\n\nThe first application will concern the quantification of the\nmagnitude of extreme surges on the Atlantic coast of Canada as par t of\nthe development of an overland flood protection product by an\ninsu rance company. The second illustration will show how coherent\nestimates o f extreme precipitation of several durations based on a\nBayesian hierarch ical spatial model enhance current methodology for\nthe construction\, at monitored and unmonitored locations\, of IDF\ncurves commonly used in inf rastructure design\, flood protection\, and\nurban drainage or water mana gement.\n\n-------------------------\n DTSTAMP:20250516T223138Z END:VEVENT END:VCALENDAR