Welcome

Marcos Oliveira Prates

Professor
Department of Statistics
Universidade Federal de Minas Gerais

Avenida Presidente Antônio Carlos, 6627, ICEX, Departamento de Estatística

– Pampulha, Belo Horizonte - Minas Gerais, 31270-901

Curriculum Vitae

I am currently a professor in the Department of Statistics at the Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. I received my PhD in Statistics in 2011 from the University of Connecticut, Storrs, USA, under the supervision of Jun Yan and Dipak K. Dey. My main research fields of interests are: Generalized Linear Mixed Models (GLMM), Bayesian Statistics, Spatial Statistics, Gaussian Markov Random Fields and Asymmetrical Distributions. I focus my research on application of these methodologies in ecological, criminal and health related problems.

Education

Professor, Universidade Federal de Minas Gerais, Brazil, current.
Post-doc. Statistics, Universidade Estadual de Campinas, Brazil, 2012.
PhD. Statistics, University of Connecticut, USA, 2011.
M.S. Statistics, Universidade Federal de Minas Gerais, Brazil, 2008.
B.S. Computational Mathematics, Universidade Federal de Minas Gerais, Brazil, 2006.

Teaching

Estatística e Probabilidade - EST031 (Spring 2012, Fall 2012, Fall 2014, Spring 2015, Spring 2016, Fall 2016, Spring 2019)
Aprendizado de Máquina - EST171(Fall 2015, Fall 2016, Fall 2018)
Modelos Lineares Generalizados - (Spring 2013, Spring 2014, Fall 2015, Spring 2017, Fall 2018)
Pacotes Estatísticos - EST008(Spring 2018)
Tópicos Avançados em R - EST171(Spring 2014, Spring 2017)
Aprendizado de Máquina - EST171(Fall 2015, Fall 2016)
Estatística I – EST180 (Spring 2012, Spring 2013, Spring 2015)
Probabilidade – EST032 (Fall 2012, Fall 2013)
Estatística e Probabilidade – EST869 (Spring 2013)
Bio-Estatística – EST612 (Spring 2012)
Estatística Espacial (Fall 2011)
STAT 3115Q (Fall 2010, Spring 2011)
STAT 3445 (Spring 2010)
STAT 3375Q (Fall 2009)

Recent Publications

Lachos, Victor H.; Cabral, Celso R. B.; Prates, Marcos O.; Dey, Dipak K.. Flexible regression modeling for censored data based on mixtures of student-t distributions. Computational Statistics, v.34, p. 123-152, 2019.
Cornejo, Zaida Q.; Prates, Marcos O.. Bayesian spatio-temporal modelling of anchovy abundance through the SPDE Approach. Spatial Statistics, v. 28, p. 236-256, 2018.
Meredith, Christy S.; Budy, Phaedra; Hooten, Mevin B. ; Prates, Marcos O.. Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach. Biological Invasions (Dordrecht. Online), v. 19, p. 503-519, 2017.
Cortes, Renan X.; Martins, Thiago G.; Prates, Marcos O.; Silva, Bráulio F. A. O.. Inference on Dynamic Models for non-Gaussian Random Fields using INLA. Brazilian Journal of Probability and Statistics, v. 31, p. 1-23, 2017.
Veloso, Bráulio M.; Correa, Thais R.; Prates, Marcos. O.; Oliveira, Gabriel F.; Tavares, André I.. MAD-STEC: a method for multiple automatic detection of space-time emerging clusters. Statistics and Computing, 2017.

Software

spGoogle - fusing R with GoogleMaps, installation script (para instalação).
rbugs – fusing R with OpenBUGS
mixsmsn - fitting finite mixture of scale mixture of skew-normal distributions
Stcd (english version) - A Shiryaev-Roberts based prospective spatio-temporal cluster detection as in Assuncao and Correa (2009). This is a stand-alone version. This method is also implemented for R in the stcd() function under the “surveillance” package. For the portuguese version click here.