[ABE-L] Seminário DEST/UFMG em 14/06/2024

[Marcos Prates]

Caros,

Na próxima sexta-feira (14 de Junho, às 13:30h) o ciclo de Seminários do
Departamento de Estatística da UFMG terá a apresentação do Prof. Aritra
Halder da Drexel University - USA.

Aritra Halder is an assistant professor of Biostatistics in the Department
of Epidemiology and Biostatistics, at the Dornsife School of Public Health,
Drexel University. He completed his PhD in Statistics from the University
of Connecticut in July, 2020. His research interests are Bayesian modeling,
Spatial and Spatiotemporal analysis, and Optimization.

Title: Bayesian Modeling with Spatial Curvature Processes

Spatial process models are widely used for modeling point-referenced
variables arising from diverse scientific domains. Analyzing the resulting
random surface provides deeper insights into the nature of latent
dependence within the studied response. We develop Bayesian modeling and
inference for rapid changes on the response surface to assess directional
curvature along a given trajectory. Such trajectories or curves of rapid
change, often referred to as wombling boundaries, occur in geographic space
in the form of rivers in a flood plain, roads, mountains or plateaus or
other topographic features leading to high gradients on the response
surface. We demonstrate fully model based Bayesian inference on directional
curvature processes to analyze differential behavior in responses along
wombling boundaries. We illustrate our methodology with a number of
simulated experiments followed by multiple applications featuring the
Boston Housing data; Meuse river data; and temperature data from the
Northeastern United States. Supplementary materials for this article are
available online.

O seminário será transmitido ao vivo pelo canal do Youtube "Seminários DEST
- UFMG".

https://www.youtube.com/@seminariosdest-ufmg

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