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].
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].