[ABE-L] Seminários PIPGEs UFSCar/USP

[Michel H. Montoril]

Caros,

No último email havia um erro no schedule do nosso próximo seminário. No
copy and paste a data ficou errada. Isso já foi corrigido na página do
seminário e agora disponibilizamos novamente aqui com a data correta. Peço
desculpas pelos múltiplos emails e agradeço aos colegas que fizeram a
gentileza de me informar. Seguem as informações corretas (tomara!) logo
abaixo.

Saudações,
Michel

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

*Video call link HERE <https://meet.google.com/cet-uari-pct>.*

*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).


===============================
/* Michel H. Montoril,
 * Assistant Professor,
 * Department of Statistics,
 * Federal University of São Carlos,
 * São Carlos, SP, 13565-905, Brazil
 */


On Tue, Nov 8, 2022 at 12:11 PM Michel H. Montoril <michelcias em gmail.com>
wrote:

> Caros,
>
> Gostaríamos de convidar a todos para o próximo seminário conjunto
> UFSCar/ICMC-USP, que ocorrerá no dia *11/11*, *às 14h*. Seguem
> informações abaixo.
>
> Saudações,
> Michel
>
> *Scheduled for:*
> Oct 21, 2022, at 2:00 pm
> (GMT-03:00) Brasilia Standard Time - Sao Paulo
>
> *Video call link HERE <https://meet.google.com/cet-uari-pct>.*
>
> *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)
> .
>
> ===============================
> /* Michel H. Montoril,
>  * Assistant Professor,
>  * Department of Statistics,
>  * Federal University of São Carlos,
>  * São Carlos, SP, 13565-905, Brazil
>  */
>
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