[ABE-L] Ciclo de Palestras - PPGE - IM/UFRJ - 18 de SETEMBRO - Vinicius Mayrink (UFMG)

[Maria Eulalia Vares]

Prezados colegas,

A nossa próxima palestra ocorrerá na quarta-feira, 18 de setembro,
*EXCEPCIONALMENTE
NO HORÁRIO DE 13H ÀS 14H30.*

Local: Sala C116 do Instituto de Matemática, Centro de Tecnologia - UFRJ.

*Palestrante: Vinicius Diniz Mayrink (UFMG)*

*Título: *Functional data analysis: spatial association of curves and
irregular spacing.


*Resumo: *Spatial Functional Data (SFD) analysis is an emerging statistical
framework that combines Functional Data Analysis (FDA) and spatial
dependency modeling. Unlike traditional statistical methods, which treat
data as scalar values or vectors, SFD considers data as continuous
functions, allowing for a more comprehensive understanding of their
behavior and variability. This approach is well-suited for analyzing data
collected over time, space, or any other continuous domain. SFD has found
applications in various fields, including economics, finance, medicine,
environmental science, and engineering. This study proposes new functional
Gaussian models incorporating spatial dependence structures, focusing
on irregularly spaced data and reflecting spatially correlated curves. The
model is based on Bernstein polynomial (BP) basis functions and utilizes a
Bayesian approach for estimating unknown quantities and parameters. The
paper explores the advantages and limitations of the BP model in capturing
complex shapes and patterns while ensuring numerical stability. The main
contributions of this work include the development of an innovative
model designed for SFD using BP, the presence of a random effect to address
associations between irregularly spaced observations, and a comprehensive
simulation study to evaluate models’ performance under various scenarios.
The work also presents one real application of Temperature in Mexico City,
showcasing practical illustrations of the proposed model.

This is a joint work with Alexander Burbano-Moreno.

Mais informações podem ser encontradas no site:
https://www.dme.ufrj.br/?page_id=3579.

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
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