Nov 11, 2022 - Some recent advances in quantile regression under the Bayesian approach - Speaker: Kelly C. M. Gonçalves (UFRJ)

UFSCar/USP joint Seminar

Announcement file.

Scheduled for:
Nov 11, 2022, at 2:00 pm
(GMT-03:00) Brasilia Standard Time - Sao Paulo

Video call link HERE.

Speaker:
Kelly C. M. Gonçalves (UFRJ)

Title:
Some recent advances in quantile regression under the Bayesian approach
 
Abstract:
Quantile regression models provide richer information on the effects of the predictors than does the traditional mean regression and it is less sensitive to heteroscedasticity and outliers, accommodating non-normal errors often encountered in practical applications. Bayesian inference for quantile regression may proceed by forming the likelihood function based on the asymmetric Laplace distribution or a generalization, and a location-scale mixture representation of it allows finding analytical expressions for the conditional posterior densities of the model. The main aim of this talk is to present quantile regression and some recent extensions.

Bio:
Kelly is an Associate Professor in the Department of Statistics at the Federal University of Rio de Janeiro (UFRJ).  She has BSc in Mathematics, MSc and PhD in Statistics from UFRJ. In 2020 she worked as a visiting researcher at University of Florida. Actually, she is also a visiting researcher at Instituto de Pesquisa Econômica Aplicada (IPEA) and member of the Sampling Advisory Committee of the Basic Education Assessment Board (DAEB) in the National Institute of Educational Studies and Research (INEP).