[ABE-L] Seminários PIPGEs UFSCar/USP

[Michel H. Montoril]

Caros,

Gostaríamos de convidar a todos para o próximo seminário conjunto
UFSCar/ICMC-USP, que ocorrerá no dia *24/06*, *às 14h*. Seguem informações
abaixo.

Sintam-se à vontade para divulgar (arquivo em anexo) entre eventuais
interessados.

Saudações,
Michel

*Scheduled for:*
Jun 24, 2022, at 2:00 pm
(GMT-03:00) Brasilia Standard Time - Sao Paulo

*Video call link HERE <https://meet.google.com/ang-rjyk-zcj>.*

*Speaker:*
Rodney Fonseca (Weizmann Institute of Science)

*Title:*
Graph wavelet variance and its properties

*Abstract:*
Many data sets have observations of signals measured on networks, and such
a graph structure must be considered when performing statistical analyses.
This is a frequent task in fields related to graphical models and graph
signal processing. We introduce graph wavelet variance to analyze random
variables observed on nodes of a graph. This new measure uses the
definition of graph wavelet transform, a well-known concept in signal
processing literature. Graph wavelet variance allows one to evaluate the
signal's variability corresponding to different scales of the graph
spectrum, which provides valuable insights into how the observations vary
across neighboring nodes. We propose an estimator for the graph wavelet
variance, discuss some of its large sample properties, and suggest two ways
of computing approximate confidence intervals. We use the proposed methods
to evaluate the dynamics of Sars-Cov-2 infection rates in Brazilian
cities. Joint work with Debashis Mondal and Aluisio Pinheiro.

*Bio:*
Since 2021 Rodney Fonseca is a postdoctoral fellow at the Weizmann
Institute of Science, in Israel. He got his Ph.D. in Statistics at the
University of Campinas (Unicamp) in 2021, under the supervision of Aluísio
Pinheiro. His earlier work was focused on nonparametric models, time
series, and regression analysis. More recently, he has also been working on
graph signal processing, high-dimensional statistics, and
communication-efficient inference.

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