https://repositorio.ufba.br/handle/ri/5201 2026-05-06T22:20:20Z https://repositorio.ufba.br/handle/ri/44456 Título: Aplicação de processos autorregressivos sazonais com valores inteiros (SINAR(1)) em dados de qualidade do ar: uma abordagem robusta Autor(es): Soares, Camila Braz Primeiro Orientador: Reisen, Valdério Anselmo Abstract: This paper investigates robust inference for the Seasonal Integer-Valued Autoregressive model (SINAR(1)), addressing the limitations of the classical Conditional Maximum Likelihood (CML) estimator under data contamination. We apply an alternative estimation approach based on Huber M-regression. Monte Carlo simulations evaluate the robustness efficiency trade-off under clean and contaminated scenarios. The robust model is more stable under contaminated scenarios, with a modest loss of efficiency under ideal conditions. An empirical application to seasonal Air Quality Index data derived from NASA’s MERRA-2 satellite reanalysis illustrates the proposed methodology, with coherent forecasting results indicating superior performance of the robust estimator. These findings highlight that robust M-regression provides a reliable alternative to likelihood-based estimation when data quality cannot be guaranteed. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação 2025-12-15T00:00:00Z https://repositorio.ufba.br/handle/ri/44401 Título: A teoria do transporte ótimo aplicada ao estudo de sistemas de funções iteradas Autor(es): Santos, Agábio Brasil dos Primeiro Orientador: Silva, Edgar Matias da Abstract: This work consists of a study of Iterated Function Systems that contract on average, using concepts and results from Optimal Transport Theory for this analysis. To support the discussion, it was necessary to revisit notions such as complete metric spaces, weak topology, as well as concepts from Measure Theory, Ergodic Theory, and Probability Theory. Within the latter, the notions of homogeneous Markov chains and the stationary measures associated with these chains are explored. Based on these preliminary concepts, optimal coupling is defined, demonstrating that, under certain conditions, the existence of such coupling is always guaranteed. The Wasserstein distance is also introduced, which plays an essential role in the subsequent results. Equipped with the tools of Optimal Transport Theory, this work investigates the stationary measures of Iterated Function Systems that contract on average, proving that, in this context, there is existence and uniqueness of a stationary measure, in addition to obtaining estimates for its moments of order q. Finally, the developed concepts are applied to the study of skew-products that have contractive fibers, showing that such systems admit a single "stationary measure'' with limited support. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação 2025-11-11T00:00:00Z https://repositorio.ufba.br/handle/ri/44277 Título: Operadores Dunford-Pettis em reticulados de Banach Autor(es): Antunes, Gleberson Gregorio da Silva Primeiro Orientador: Ribeiro, Joilson Oliveira Abstract: A Dunford–Pettis operator is a linear operator that maps weakly convergent sequences into norm-convergent sequences. This work investigates the properties of positive operators defined on Banach lattices, with an emphasis on domination results. Specifically, we analyze the behavior of operators S and T satisfying 0 ≤ S ≤ T, seeking to determine how the properties of the dominating operator T, such as compactness or being a Dunford–Pettis operator, influence the operator S and its powers. Editora / Evento / Instituição: UNIVERSIDADE FEDERAL DA BAHIA Tipo: Dissertação 2026-02-24T00:00:00Z https://repositorio.ufba.br/handle/ri/44276 Título: Testes não paramétricos em análise de sobrevivência no contexto de inferência causal Autor(es): Azevedo, Arthur Rios de Primeiro Orientador: Amorim, Leila Denise Alves Ferreira Abstract: Research aimed at estimating causal effects of interventions on time-to-event outcomes in observational studies faces challenges, notably when the goal is to compare groups in the presence of confounding. Propensity score–based methodologies are well established in the literature and provide a robust framework for causal inference in observational studies. Weighting procedures have already been employed in nonparametric methods, such as the Kaplan-Meier estimator, allowing the construction of pseudo-populations using propensity scores, which yield adjusted, unbiased estimates in the presence of confounding. However, their integration with nonparametric hypothesis tests in survival analysis is still limited to the Log-Rank test and remains an area in need of methodological developments. In this dissertation, a generalization of nonparametric tests adjusted by the inverse probability of treatment weighting is developed, with a focus on comparing survival functions under different hazard patterns. The proposed methodology is assessed through simulation studies that consider alternative hypotheses involving proportional hazards, early and late separation, and crossing survival curves, as well as different censoring and sample size scenarios. The results show substantial gains in test power when the separation pattern is aligned with the weighting scheme used, suggesting that tests adjusted with appropriate weights can outperform classical approaches in the detection of causal effects. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação 2025-12-18T00:00:00Z