Please Note: This seminar will be given online.
Distinguished Lecture Series
Christian Genest, Canada Research Chair in Stochastic Dependence Modeling, Professor
Bayesian Hierarchical Modeling of Spatial Extremes
Climate change and global warming have increased the need to assess and forecast environmental risk over large domains and to develop models for the extremes of natural phenomena such as droughts, ﬂoods, torrential precipitation, and heat waves. Because catastrophic events are rare and evidence is limited, Bayesian methods are well suited for the areal analysis of their frequency and size. In this talk, a multi-site modeling strategy for extremes will be described in which spatial dependence is captured through a latent Gaussian random ﬁeld whose behavior is driven by synthetic covariates from climate reconstruction models. It will be seen through two vignettes that the site-to-site information sharing mechanism built into this approach does not only generally improve inference at any location but also allows for smooth interpolation over large, sparse domains.
The ﬁrst application will concern the quantiﬁcation of the magnitude of extreme surges on the Atlantic coast of Canada as part of the development of an overland ﬂood protection product by an insurance company. The second illustration will show how coherent estimates of extreme precipitation of several durations based on a Bayesian hierarchical spatial model enhance current methodology for the construction, at monitored and unmonitored locations, of IDF curves commonly used in infrastructure design, ﬂood protection, and urban drainage or water management.
Christian Genest is Professor of Statistics, Canada Research Chair in Stochastic Dependence Modeling, and a fellow of the Trottier Institute for Science and Public Policy at McGill University. A graduate of the University of British Columbia (1983), he held previous posts at Carnegie-Mellon University (1983-84), the University of Waterloo (1984-87), and Université Laval (1987-2010). His main research interests are in multivariate analysis, nonparametric inference, and extreme-value theory. He has published in a broad range of journals and collaborates often with researchers in ﬁnance, insurance, and environmental science. He is a pioneer of the copula approach to dependence modeling and his work in the area is widely cited. He was the 2011 recipient of the Statistical Society of Canada Gold Medal and was elected a Fellow of the Royal Society of Canada in 2015. He received a Humboldt Research Prize in 2019 and the 2020 John L. Synge Award. He has also served in numerous professional and editorial capacities, notably as President of the Statistical Society of Canada (2007-08) and Editor-in-Chief of the Journal of Multivariate Analysis (2015-19).
David A. Sprott (1930-2013)
Professor David Sprott was the first Chair (1967-1975) of the Department of Statistics and Actuarial Science at the University of Waterloo and first Dean of the Faculty of Mathematics (1967-1972). The David Sprott Distinguished Lecture Series was created in recognition of his tremendous leadership at a formative time of our department, as well as his highly influential research in statistical science.