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Ph.D. in Statistics

​2010 - 2015

 

My Ph.D. thesis work focused on modeling and prediction of time series of binary network data. The primary interests were to identify events associated with structural changes in the network, and performing short-term link prediction of the network in future periods. The work was applied to financial trading networks from the natural gas futures market in the New York Mercantile Exchange (NYMEX).

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M.S. in Mathematics (Statistics track)

​2006 - 2008

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My master's project focused on objective Bayesian methods for population genetics where we developed an intrinsic prior for testing of Hardy-Weinberg equilibrium. The main goal of this work was to provide geneticists with a default Bayesian procedure for hypothesis testing of equilibrium.

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B.S. in Statistics

​2001 - 2005

 

​I received training in classical statistics including multivariate analysis, nonparametric statistics, experimental design and survey sampling. 

Anchor 1
Skills

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LaTeX 

R Markdown

R package development

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Programming Languages

R

C++

Rcpp

SAS

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Research
Interests

My research interests include record linkage, machine learning, Bayesian nonparametric methods, network analysis, weakly informative priors and efficient Bayesian algorithms. 

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I have experience with methods that include partition models for record linkage, Stochastic blockmodels for random graphs, time series models, generalized linear models, penalized regression, coordinate descent algorithms, discrete latent variable models, parallel computing and MCMC algorithms.

Education
Publications

  • Betancourt B., Rodríguez A., Boyd N.(2017+) "Modeling and Prediction of Financial Trading Networks: A case study in the NYMEX natural gas futures market". In revision for Journal of Royal Society Series C. arXiv:1710.01415

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  • Betancourt B., Rodríguez A., Boyd N. (2017). "Bayesian Fused Lasso regression for dynamic binary networks".  Journal of Computational and Graphical Statistics . In Press. doi:10.1080/10618600.2017.1341323

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  • Betancourt B., Rodríguez A., Boyd N. (2017). "Investigating competition in financial markets: a sparse autologistic model for dynamic network data". Journal of Applied Statistics. In Press. doi:10.1080/02664763.2017.1357684

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  • Fuquene, J., Betancourt, B., Pereira, J. B. M. (2017). "A weakly informative prior for Bayesian dynamic model selection with applications in fMRI". Journal of Applied Statistics. In Press. doi:10.1080/02664763.2017.1363161

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  • Betancourt B, Steorts R. (2017). Bayesian Decision Making with Application to Resource Allocation (Invited paper), Wiley StatsRef-Statistics Reference Online, In Press.

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  • Zanella, G., Betancourt, B., Wallach, H., Miller, J., Zaidi, A. and Steorts, R. (2016)."Flexible Models for Microclustering with Applications to Entity Resolution", Advances in Neural Information Processing Systems (NIPS) , Vol. 29,  pp 1417-1425. arXiv:1610.09780

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  • Miller J.W., Betancourt B., Zaidi A., Walach H., Steorts R. (2015). "The Microclustering Problem: When the Cluster Sizes Don't Grow with the Number of Data Points". NIPS Bayesian Nonparametrics: The Next Generation Workshop Series. arXiv:1512.00792 

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  • Fuquene J., Betancourt B., Vega J. (2011). "Heavy tailed priors: An alternative to non-informative priors in the estimation of proportions on small areas". Biometrics Brazilian Journal, v.29, n.3, pg 520-533 . arXiv:1107.2724

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