Eduardo Janotti Cavalcante
São Paulo Research Foundation (FAPESP), Brazil
CEAUL, Faculdade de Ciências, Universidade de Lisboa
Ciências ULisboa, C6, Floor 2, Room 6.2.33
& online
15 June 2026 (Monday) – 14h00
Abstract:
Survival modeling often requires extrapolation beyond observed follow-up periods, making long-term dynamics difficult to characterize reliably. Existing approaches typically rely on restrictive assumptions, such as cure-rate formulations or constrained tail specifications, which can limit extrapolation performance.
We propose a Bayesian semiparametric survival model that combines Extreme Value Theory (EVT) with latent Gaussian processes, enabling the joint modeling of central and extreme hazard behavior without threshold selection. The framework accommodates a flexible, covariate-dependent extreme value index while avoiding strong parametric assumptions.
Using survival data from InCor, we show that the proposed approach improves the representation of long-term hazard dynamics while maintaining coherence across the hazard function. The resulting methodology provides a flexible and practical tool for settings where accurate tail characterization is essential.
Short bio:
Eduardo is a PhD candidate in Probability and Statistics at the University of São Paulo (USP) and is currently undertaking a doctoral research visit at the Faculty of Sciences of the University of Lisbon. His research interests lie in socio-environmental statistics, with particular emphasis on network analysis, sub-asymptotic behavior, nonstationarity, nonlinear modeling, nonparametric methods, risk analysis, reliability, survival analysis, and extreme value theory. His current research focuses on the intersection of survival analysis and extreme value methods.
This work is supported by the São Paulo Research Foundation (FAPESP), Brazil, under Grant Nos. 2025/10342-3 and 2025/22925-3. Additional support is provided by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., under CEAUL Research Unit, UID/00006/2025, DOI: https://doi.org/10.54499/UID/00006/2025, and by the European Union – NextGenerationEU through the project UID/PRR/00006/2025, DOI: https://doi.org/10.54499/UID/PRR/00006/2025.
