Wagner Hugo Bonat is Researcher and Lecturer of the Department of Statistics at Paraná Federal University - UFPR, where he has been since 2010. He is the Head of the Data Science and Big Data program (DSBD) and a member of the Laboratory of Statistics and Geoinformation (LEG). He received a B.S. from Paraná Federal University in 2008, and an M.S. from the Paraná Federal University in 2010. He received his Ph.D. in Mathematics and Computer Science from the University of Southern Denmark in 2016.
His research lies on statistical modelling and estimating functions. Much of his work has been on extending the generalized linear model class to deal with multiple response variables. His main contribution is a new class of multivariate regression models called Multivariate Covariance Generalized Linear models (McGLMs) and the associated R package (mcglm).
PhD in Mathematics and Computer Science, 2016
University of Southern Denmark - SDU
MSc in Numerical Methods in Engineering, 2010
Universidade Federal do Paraná
BSc in Statistics, 2008
Universidade Federal do Paraná
Mon, Feb 19, 2018, Workshop on Multivariate Count Analysis.
The main goal of this project is to propose a new class of multivariate regression models to deal with Gaussian and non-Gaussian data.
The main goal of this project is to construct multivariate probability distributions based on the class of exponential dispersion models.
The main goal of this project is to explore the McGLM framework for the analysis of non-trivial data sets and improving the implementation of the mcglm package for the statistical software R.
Código | Disciplina | Curso | Turma | Ano | Semestre |
---|---|---|---|---|---|
CE224 | Métodos Computacional para Inferência | Estatística | EST | 2019 | 1 |