Marco A.R. Ferreira

STAT 5544 (Fall 2014)

• Highly structured models: multi-scale models, spatial-temporal models, Markov random fields, state-space models
• Bayesian Statistics
• Computational statistics: Markov chain Monte Carlo, simulated annealing and genetic algorithms
• Inverse problems: solution and uncertainty characterization
• Applications to environment, medicine, epidemiology

• T.C.O. Fonseca and M.A.R. Ferreira (2017), Dynamic Multiscale Spatiotemporal Models for Poisson Data, Journal of the American Statistical Association, vol. 112, 215--234.
• N. Sanyal and M.A.R. Ferreira (201X), Bayesian Wavelet Analysis Using Nonlocal Priors with an Application to fMRI analysis, Sankhya -- Series B, to appear.
• Andrew Hoegh, Marco A.R. Ferreira, and Scotland Leman (2016), Spatiotemporal Model Fusion: Multiscale Modeling of Civil Unrest, Journal of the Royal Statistical Society - Series C, vol. 65, 529--545.
• C.T. Rota, M.A.R. Ferreira, R.W. Kays, T.D. Forrester, E.L. Kalies, W.J. McShea, A.W. Parsons, J.J. Millspaugh (2016), A multi-species occupancy model for two or more interacting species, Methods in Ecology and Evolution, vol. 7, 1164-1173.
• Ho-Hsiang Wu, Marco A.R. Ferreira, and M.E. Gompper (2016), Consistency of hyper-g-prior-based Bayesian variable selection for generalized linear models, Brazilian Journal of Probability and Statistics, vol. 30, 691--709.
• M. C. T. Santos, A. N. Tegge, B. R. Correa, S. Mahesula, L. Q. Kohnke, M. Qiao, M. A. R. Ferreira, E. Kokovay and L. O. F. Penalva (2016), miR-124, -128 and -137 orchestrate neural differentiation by acting on overlapping gene sets containing a highly connected transcription factor network, Stem Cells, vol. 34, 220-232.
• Marco A.R. Ferreira (2015), Inhomogeneous evolutionary MCMC for Bayesian optimal sequential environmental monitoring, Environmental and Ecological Statistics, vol. 22, 705-724.
• Shiqi Cui, Subha Guha, Marco A.R. Ferreira, and Allison N. Tegge (2015), A Hidden Markov Model for Detecting Differentially Expressed Genes from RNA-Seq Data, Annals of Applied Statistics, vol. 9, 901-925.
• Marco A.R. Ferreira (201X), Inhomogeneous evolutionary MCMC for Bayesian optimal sequential environmental monitoring, Environmental and Ecological Statistics, to appear.
• Marco A.R. Ferreira and Nilotpal Sanyal (2014), Bayesian optimal sequential design for nonparametric regression via inhomogeneous evolutionary MCMC, Statistical Methodology, vol. 18, 131-141.
• Marco A.R. Ferreira, M.A. Jaramillo (2014), Bayesian multiscale phylogenetics, Journal of the Indian Society of Agricultural Statistics (Special issue on large and massive datasets), vol. 68, 285-292.
• Marco A.R. Ferreira and Esther Salazar (2014), Bayesian reference analysis for exponential power regression models, Journal of Statistical Distributions and Applications (Special issue for ICOSDA 2013), 1:12.
• Dmitriy Karpman, Marco A.R. Ferreira, Christopher K. Wikle (2013), A Point Process Model for Tornado Report Climatology, Stat, vol. 2, 1-8.
• Marco A.R. Ferreira (2013), Invited discussion on Large covariance estimation by thresholding principal orthogonal complements by J. Fan, Y. Liao, M. Mincheva, Journal of the Royal Statistical Society - Series B, vol. 75, 603-680.
•  Nilotpal Sanyal and Marco A.R. Ferreira (2012), Bayesian Hierarchical Multi-subject Multiscale Analysis of Functional MRI Data, NeuroImage, vol. 63, 1519-1531.
• Esther Salazar, Marco A.R. Ferreira and Helio S. Migon (2012), Objective Bayesian Analysis for the Exponential Power Regression Model, Sankhya - Series B, vol. 74, 107-125.
• Ramiro Ruiz-Cardenas, Marco A.R. Ferreira and Alexandra M. Schmidt (2012), Evolutionary Markov Chain Monte Carlo Algorithms for Optimal Monitoring Network Designs, Statistical Methodology (Special Issue on Astrostatistics and Spatial Statistics), vol. 9, 185-194.
• Marco A.R. Ferreira (2012), Invited Discussion of Spatial quantile multiple regression using the asymmetric Laplace process by K. Lum and A. E. Gelfand, Bayesian Analysis, vol. 7, 235-276.
• Thais C.O. Fonseca, Helio S. Migon and Marco A.R. Ferreira (2012), Bayesian analysis based on the Jeffreys prior for the hyperbolic distribution, Brazilian Journal of Probability and Statistics (Special Issue for the 2010 Bayesian Brazilian Meeting), vol. 26, 327-343.
• Marco A.R. Ferreira, Scott H. Holan and Adelmo I. Bertolde (2011), Dynamic Multiscale Spatio-Temporal Models for Gaussian Areal Data, Journal of the Royal Statistical Society - Series B, vol. 73, 663-688.
• Marco A.R. Ferreira (2011), Invited Discussion on Characterizing Uncertainty of Future Climate Change Projections Using Hierarchical Bayesian Models by Claudia Tebaldi, Richard L. Smith and Bruno Sansó, in Bayesian Statistics 9, (Editors: J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West), 639-658, Oxford University Press.
• Esther Salazar and Marco A.R. Ferreira (2011), Temporal Aggregation of Lognormal Autoregressive Processes, Journal of Time Series Analysis, vol. 32, 661-671.
• Victor de Oliveira and Marco A.R. Ferreira (2011), Maximum Likelihood and Restricted Maximum Likelihood Estimation for a Class of Gaussian Markov Random Fields, Metrika, vol. 74, 167-183.
• Marco A.R. Ferreira (2011), Invited Discussion on An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach by F. Lindgren, H. Rue, and J. Lindstrom, Journal of the Royal Statistical Society - Series B, vol. 73, pp 423-498.
• Marco A.R. Ferreira, Adelmo I. Bertolde and Scott H. Holan (2010), Analysis of economic data with multi-scale spatio-temporal models, Handbook of Applied Bayesian Analysis, (Editors: O'Hagan and West), 295-318, Oxford University Press.
• Scott H. Holan, Daniell Toth, Marco A.R. Ferreira, and Alan F. Karr (2010), Bayesian Multiscale Multiple Imputation with Implications for Data Confidentiality, Journal of the American Statistical Association, vol. 105, 564-577.
• Ramiro Ruiz-Cardenas, Marco A.R. Ferreira and Alexandra M. Schmidt (2010), Stochastic Search Algorithms for Optimal Monitoring Network Designs, Environmetrics, vol. 21, 102-112.
• Mariane B. Alves, Dani Gamerman and Marco A.R. Ferreira (2010), Transfer Functions in Dynamic Generalized Linear Models, Statistical Modelling, vol. 10, 3-40.
• Juan C. Vivar and Marco A.R. Ferreira (2009), Spatio-temporal models for Gaussian areal data, Journal of Computational and Graphical Statistics, vol. 18, 658-674.
• Marco A.R. Ferreira (2009), Invited Discussion on Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations by H. Rue, S. Martino and Nicolas Chopin, Journal of the Royal Statistical Society - Series B, vol. 71, 319-392.
• Thais C.O. Fonseca, Marco A.R. Ferreira and Helio S. Migon (2008), Objective Bayesian analysis for the Student-t regression model, Biometrika, vol. 95, 325-333.
• Marco A.R. Ferreira and Marc A. Suchard (2008), Bayesian Analysis of Elapsed Times in Continuous-Time Markov Chains, Canadian Journal of Statistics, vol. 36, 355-368.
• Marco A.R. Ferreira and Herbert K.H. Lee (2007), Multiscale Modeling: A Bayesian Perspective, Springer Series in Statistics, New York: Springer.
• Marco A.R. Ferreira and Victor de Oliveira (2007), Bayesian reference analysis for Gaussian Markov Random Fields, Journal of Multivariate Analysis, vol. 98, 789-812.
• Ramiro Ruiz, Marco A.R. Ferreira and Alexandra M. Schmidt (2007), Evolutionary Markov chain Monte Carlo algorithms for optimal monitoring network designs, Proceedings of the Joint Statistical Meetings 2007, Section on Bayesian Statistical Science, 1332-1338.
• Marco A.R. Ferreira, Mike West, Herbert K.H. Lee and David Higdon (2006), Multi-scale and hidden resolution time series models, Bayesian Analysis, vol. 1, n. 4, 947-968.
• Migon, H.S., Gamerman, D., Lopes, H.F. and Ferreira, M.A.R. (2005), Bayesian Dynamic Models, In Handbook of Statistics, Volume 25: Bayesian Thinking, Modeling and Computation, 553-588, (Editors Dey, D. and Rao, C.R.), Elsevier, Amsterdam.
• Marco A.R. Ferreira (2005), Invited Discussion on Conceitos Estatisticos: Reflexoes by Carlos A. B. Pereira, (in Portuguese), Revista Brasileira de Estatistica, vol. 66, 7-49.
• Marco A.R. Ferreira, Mike West, Herbert K.H. Lee, David Higdon and Zhuoxin Bi (2003), Multi-scale modeling of 1-D permeability fields, in Bayesian Statistics 7, (Editors: Bernardo, Berger, Dawid and Smith), pp. 519-527. Oxford University Press.
• Herbert K.H. Lee, David Higdon, Zhuoxin Bi, Marco A.R. Ferreira and Mike West (2002), Markov random field models for high-dimensional parameters in simulations of fluid flow in porous media, Technometrics, vol. 44, n. 3, 230-241.
• Fernando A.S. Moura, Helio S. Migon and Marco A.R. Ferreira (2000), Small area estimation for binary data via Bayesian Hierarchical Models, Statistics in Transition, vol. 4, n. 4, 665-677.
• Marco A.R. Ferreira and Dani Gamerman (2000), Dynamic Generalized Linear Models, in Generalized Linear Models: a Bayesian Perspective, pp. 57-72, (Editors: Dey, Ghosh and Mallick), Marcel Dekker, New York.
• Herbert K.H. Lee, David Higdon, Zhuoxin Bi, Marco A.R. Ferreira and Mike West (2000), Markov random field models for high-dimensional parameters in simulations of fluid flow in porous media, Proceedings of the Joint Statistical Meetings (Award of Best Contributed Paper by the Statistical Computing Section).
• Marco A.R. Ferreira and Dani Gamerman (1999), Bayesian analysis of epidemiologic count series via dynamic generalized Bayesian models (In Portuguese), Cadernos de Saude Coletiva, vol. 6, 145-155.
• Marco A.R. Ferreira, Dani Gamerman and Helio S. Migon (1997), Bayesian Dynamic Hierarchical Models: Covariance Matrices Estimation and Nonnormality, Brazilian Journal of Probability and Statistics, vol. 11, 67-79.
• Marco A.R. Ferreira (1997), Predictive distribution and model comparison (In Portuguese), Bulletin of the Brazilian Statistical Association, vol. 38, 28-31.