CV Lattes
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Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Undergratuated in Statistics from Universidade Estadual de Campinas (1979) where he received the Master degree in Statistics in 1982. He was contracted in 1983 as Assistent Professor in the Statistics Department of Universidade de São Paulo where he got the PhD degree in Statistics in 1988. From 1992-94 he was Visiting Scholar in the Biostatistics Department of University of North Carolina at Chapel Hill. He is since 2007 Full Professor in the Statistics Department of Universidade de São Paulo. He published over 80 peer-reviewed papers in international journals of Statistics such as ANZJS, Biometrics, Biometrika, BJournal, BJPS, Computational Statistics, CSDA, CS, EnvironMetrics, ISR, JAS, JRSS-B, JRSS-D, JSCS, JSPI, LIDA, Statistical Modelling, Statistical Papers and TEST, among others, and received over 3500 citations in Google Scholars (h-index=33) and over 1500 citations in each base SCOPUS and Web of Science. He was AE of CSDA from 2003-2016 and he is since 2003 AE of the Brazilian Journal of Probability and Statistics and since 2019 AE of the São Paulo Journal of Mathematical Sciences. He is Co-editor of the book series SpringerBriefs in Statistics of the Brazilian Statistical Association since 2016. He supervised 22 PhD students, 18 Master students, and 2 posdocs, and he has experience in Statistical Methods, acting in the following subjects: generalized linear models, mixed models, diagnostic methods, symmetric and asymmetric models, semiparametric models, generalized estimating equations. GAMLSS and survival analysis models. (Source: Lattes Curriculum)
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This project aims to study associations among sets of variables using statistical methodologies based on regression models. In this context, we deal with topics that, in the statistical literature, are known as survival analysis, mixed models, beta regression models, item response theory, etc. In particular, we intend to study different formulations for such models, several estimation met…
The theme of this project is the study of the association between sets of variables. With this goal, we use statistical methodology based on regression models, understood, here, in a broad sense. Under this perspective, we deal with topics that ... (AU)
The theme of this project is the study of the association between sets of variables. With this goal, we use statistical methodology based on regression models, understood, here, in a broad sense. Under this perspective, we deal with topics that, in the statistical literature are known as Analysis of Categorical Data, Survival Analysis, Regression Analysis, etc. In particular, we intend to…
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In this project we propose the investigation of important issues related to the nonlinear mixed-effects modeling assuming elliptical errors, including the assumption of heteroscedastic and/or autoregressive structures as a generalization of the scale matrix from the models developed by the applicant Cibele Russo in her Doctorate Thesis and published in Computational Statistics and Data An…
The aim of this work is to extend some topics investigated in the Doctor Thesis by German Pulgar related with additive semiparametric mixed models with elliptical errors. Especifically we intend to investigate nonlinear semiparametric mixed models with elliptical errors based on penalized likelihood functions. From such functions we will obtain the correspondig score functions and the Fis…
In this project we discuss the development and analysis of nonlinear elliptical models, which represents a new methodology for obtaining robust estimates to nonlinear correlated data. The nonlinear models have been widely used, but little can be found using the elliptical approach. We intend to consider models which were previously analysed under normality, but that presented heavy tail w…
| 6 / 5 | Completed research grants |
| 3 / 3 | Completed scholarships in Brazil |
| 1 / 0 | Completed scholarships abroad |
| 10 / 8 | All research grants and scholarships |
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