Andrés Felipe Barrientos

Assistant Professor
Department of Statistics
Florida State University

Refereed Journals

Wehrhahn, C., Barrientos, A. F., and Jara, A. (2022). Dependent Bayesian nonparametric modeling of compositional data using random Bernstein polynomials. Electronic Journal of Statistics, 16(1):2346–2405. [Link].

Barrientos, A. F., Sen, D., Page, G. L., and Dunson, D. B. (2022). Bayesian inferences on uncertain ranks and orderings: Application to ranking players and lineups. Bayesian Analysis, forthcoming. [arXiv]

Nixon, M. P., Barrientos, A. F., Reiter, J. P., and Slavković, A. (2022). A latent class modeling approach for differentially private synthetic data for contingency tables. Journal of Privacy and Confidentiality, forthcoming. [arXiv]

Wehrhahn, C., Jara, A., and Barrientos, A. F. (2021). On the small sample behavior of Dirichlet process mixture models for data supported on compact intervals. Communications in Statistics - Simulation and Computation, 50(3):786–810. [Link].

Barrientos, A. F. and Canale, A. (2021). A Bayesian goodness-of-fit test for regression. Computational Statistics & Data Analysis, 155:107104. [Link].

Iguchi, T., Barrientos, A. F., Chicken, E., and Sinha, D. (2021). Nonlinear profile monitoring with single index models. Quality and Reliability Engineering International, 37(7):3004–3017. [Link].

Barrientos, A. F. and Peña, V. (2020). Bayesian bootstraps for massive data. Bayesian Analysis, 15(2):363-388. [Link].

Barrientos, A. F., Reiter, J. P., Machanavajjhala, A., and Chen, Y. (2019). Differentially private significance tests for regression coefficients. Journal of Computational and Graphical Statistics, 28(2):440–453. [Link].

Akande, O., Barrientos, A. F., and Reiter, J. P. (2019). Simultaneous edit and imputation for household data with structural zeros. Journal of Survey Statistics and Methodology, 7(4):498–519. [Link].

Akande, O., Reiter, J. P., and Barrientos, A. F. (2018). Multiple imputation of missing values in household data with structural zeros. Survey Methodology, 45(2):271–294. [Link].

Gutiérrez, L., Barrientos, A. F., González, J., and Taylor-Rodríguez, D. (2019). A Bayesian nonparametric multiple testing procedure for comparing several treatments against a control. Bayesian Analysis, 14(2):649-675. [Link].

Barrientos, A. F., Bolton, A., Balmat, T., Reiter, J. P., de Figueiredo, J. M., Machanavajjhala, A., Chen, Y., Kneifel, C., DeLong, M. (2018). Providing access to confidential research data through synthesis and verification: An application to data on employees of the U.S. federal government. The Annals of Applied Statistics, 12(2):1124–1156. [Link].

Chen, Y., Barrientos, A. F., Machanavajjhala, A., and Reiter, J. P. (2018). Is my model any good: differentially private regression diagnostics. Knowledge and Information Systems, 54(1):33–64. [Link].

Barrientos, A. F., Jara, A., and Quintana, F. A. (2017). Fully nonparametric regression for bounded data using dependent Bernstein polynomials. Journal of the American Statistical Association, 112(518):806–825. [Link].

Barrientos, A. F., Jara, A., and Wehrhahn, C. (2017). Posterior convergence rate of a class of Dirichlet process mixture model for compositional data. Statistics & Probability Letters, 120:45–51. [Link].

Barrientos, A. F., Jara, A., and Quintana, F. A. (2015). Bayesian density estimation for compositional data using random Bernstein polynomials. Journal of Statistical Planning and Inference, 166:116–125. [Link].

González, J., Barrientos, A. F., and Quintana, F. A. (2015). Bayesian nonparametric estimation of test equating functions with covariates. Computational Statistics & Data Analysis, 89:222–244. [Link].

Barrientos, A. F., Jara, A., Quintana, F. A. (2012). On the support of MacEachern’s dependent Dirichlet processes and extensions. Bayesian Analysis, 7(2):277–310. [Link].

Barrientos, A. F., Olaya, J., and González, V. (2007). A spline model for electricity demand forescasting. Revista Colombiana de Estadística (Colombian Journal of Statistics), 30(2):187–202. [Link].

Refereed Conference Proceedings and Book Chapters

Chen, Y., Machanavajjhala, A., Reiter, J. P., and Barrientos, A. F. (2016). Differentially private regression diagnostics. Proceedings of the IEEE International Conference on Data Mining 2016,, ICDM, 81–90. [Link].

González, J., Barrientos, A. F., and Quintana, F. A. (2014). A dependent Bayesian nonparametric model for test equating. In Quantitative Psychology Research: The 78th Annual Meeting of the Psychometric Society, pages 213–226. Springer International Publishing. [Link].