[ABE-L] Ciclo de Palestras - PPGE-IM/UFRJ - 29 de Outubro

[Maria Eulalia Vares]

Prezados colegas,


A nossa próxima palestra ocorrerá na quarta-feira, 29 de OUTUBRO.

Local: Laboratório de Sistemas Estocásticos (LSE), Sala I-044-B, Centro de
Tecnologia - UFRJ.

Especialmente nesta data, teremos um seminário duplo, com a seguinte agenda:

- 14h00 às 15h15

*Palestrante*: Sugnet Lubbe (Stellenbosch University)
*Título*: Multi-dimensional visualisations with biplotEZ
*Resumo*: Biplots can be viewed as multi-dimensional scatterplots. The rows
of a data matrix are represented as sample points while the columns are
represented as variable axes. Although the interpretation in terms of
samples and variable axes dates from the work of Gower in the 1990’s, the
application has be limited by the availability of EZ-to-use software. In
this presentation we will look at the basic linear algebra behind two of
the most popular forms of biplots: Principal Component Analysis (PCA)
biplots and Canonical Variate Analysis (CVA) biplots. Some interesting
applications will be used to illustrate the construction of biplots with
the biplotEZ R package. Challenges that result from the visualisation of
big data will also be discussed as well as some possible solutions.

- 15h15 às 15h30 Coffee break

- 15h30 às 16h45


*Palestrante: *Marcus Nascimento (EMap/FGV)

*Título*: An Expectation-Maximization algorithm for noncrossing Bayesian
quantile regression analysis under informative sampling

*Resumo*: When quantiles are fitted separately, the resultant regression
lines may cross, violating the basic probabilistic rule that quantiles are
monotonic functions and possibly causing problems for inference and
interpretation in practice. This article introduces a method for handling
crossing issues regarding the analysis of complex survey data under
informative sampling. Using the location-scale mixture representation of
the asymmetric Laplace distribution, we write a joint posterior density
function for the quantile levels of interest and develop a constrained
Expectation-Maximization algorithm. A model-based simulation study is
proposed, and data from the Brazilian National Demographic Health Survey of
Women and Children is analyzed to verify and illustrate the algorithm’s
effectiveness.

Mais informações:
https://ppge.im.ufrj.br/ciclo-de-palestras-segundo-semestre-de-2025/

Organizadores: Maria Eulalia Vares e Widemberg S Nobre

Atenciosamente,



-- 
Maria Eulalia Vares
Professora Titular - Instituto de Matemática - UFRJ
Coordenadora do Programa de Pós-Graduação em Estatística
https://ppge.im.ufrj.br/
-------------- Próxima Parte ----------
Um anexo em HTML foi limpo...
URL: <http://lists.ime.usp.br/pipermail/abe/attachments/20251025/280c5808/attachment-0001.htm>