Miguel de Carvalho - A Bayesian Lasso for Black Swan Events
|Dates:||10 November 2021|
|Times:||14:00 - 15:00|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
|Speaker:||Miguel de Carvalho|
Miguel de Carvalho, Reader in Statistics in the School of Mathematics, University of Edinburgh is our speaker for the Statistics seminar series.
Title: A Bayesian Lasso for Black Swan Events
Abstract: In this talk, I will introduce a novel regression model for the conditional left and right tail of a possibly heavy-tailed response. The proposed model can be used to learn the effect of covariates on an extreme value setting via a Lasso-type specification based on a Lagrangian restriction. Our model can be used to track if some covariates are significant for the lower values, but not for the (right) tail—and vice-versa; in addition to this, the proposed model bypasses the need for conditional threshold selection in an extreme value theory framework. Rainfall data are used to showcase how the proposed method can learn to distinguish between key drivers of moderate rainfall, against those of extreme rainfall. Joint work with S. Pereira, P. Pereira & P. de Zea Bermudez.
Short Bio: Miguel de Carvalho is Reader in Statistics at the University of Edinburgh. He is the current President of the Portuguese Statistical Society, and a former Director of the Centre for Statistics—University of Edinburgh. Miguel is an Associate Editor for the Journal of the American Statistical Association, Annals of Applied Statistics, and Computational Statistics & Data Analysis. His research interests include, inter alia, extreme value theory and Bayesian analysis.
Miguel de Carvalho
Organisation: University of Edinburgh
Travel and Contact Information
Zoom link: https://zoom.us/j/92947173491