Andrés F. Barrientos

发表

Is my model any good: differentially private regression diagnostics

Ashwin Machanavajjhala, Jerome P. Reiter, Yan Chen, 2017, Knowledge and Information Systems.

Bayesian nonparametric estimation of test equating functions with covariates

Jorge González, Fernando A. Quintana, Andrés F. Barrientos, 2015, Comput. Stat. Data Anal..

Differentially Private Regression Diagnostics

Ashwin Machanavajjhala, Jerome P. Reiter, Yan Chen, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Nonlinear profile monitoring with single index models

Eric Chicken, Andrés F. Barrientos, Debajyoti Sinha, 2021, Qual. Reliab. Eng. Int..

On the small sample behavior of Dirichlet process mixture models for data supported on compact intervals

Andrés F. Barrientos, Alejandro Jara, Claudia Wehrhahn, 2019, Commun. Stat. Simul. Comput..

On the Support of MacEachern’s Dependent Dirichlet Processes and Extensions

Fernando A. Quintana, Andrés F. Barrientos, Alejandro Jara, 2012 .

Bayesian density estimation for compositional data using random Bernstein polynomials

Fernando A. Quintana, Andrés F. Barrientos, Alejandro Jara, 2015 .

A Dependent Bayesian Nonparametric Model for Test Equating

Fernando A. Quintana, Andrés F. Barrientos, F. Quintana, 2015 .

Fully Nonparametric Regression for Bounded Data Using Dependent Bernstein Polynomials

Fernando A. Quintana, Andrés F. Barrientos, Alejandro Jara, 2017 .

A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control

Andrés F. Barrientos, D. Taylor-Rodríguez, Luis Gutiérrez, 2019, Bayesian Analysis.

Multiple Imputation of Missing Values in Household Data with Structural Zeros

Jerome P. Reiter, Andrés F. Barrientos, O. Akande, 2017, 1707.05916.

A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government

Ashwin Machanavajjhala, Jerome P. Reiter, Yan Chen, 2017 .

Profile Monitoring via Eigenvector Perturbation

Andrés F. Barrientos, D. Sinha, E. Chicken, 2022, 2205.15422.

Bayesian Bootstraps for Massive Data

Andrés F. Barrientos, V'ictor Pena, 2017, Bayesian Analysis.

Nonparametric Bayesian Approach to Treatment Ranking in Network Meta-Analysis with Application to Comparisons of Antidepressants

Andrés F. Barrientos, Lifeng Lin, G. Page, 2022, 2207.06561.

Differentially Private Hypothesis Testing with the Subsampled and Aggregated Randomized Response Mechanism

Andrés F. Barrientos, V'ictor Pena, 2022, 2208.06803.

Differentially Private Methods for Compositional Data

Andrés F. Barrientos, Qi Guo, 2022, 2211.06337.

A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses for Administrative Tax Data

Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke, 2021, 2110.12055.

A Bayesian goodness-of-fit test for regression

Antonio Canale, Andrés F. Barrientos, Andrés F. Barrientos, 2021, Comput. Stat. Data Anal..

A Latent Class Modeling Approach for Generating Synthetic Data and Making Posterior Inferences from Differentially Private Counts

Jerome P. Reiter, Andrés F. Barrientos, Michelle Pistner Nixon, 2022, 2201.10545.

Posterior convergence rate of a class of Dirichlet process mixture model for compositional data

Andrés F. Barrientos, A. Jara, Claudia Wehrhahn, 2017 .

Mixture representations for likelihood ratio ordered distributions

David S. Matteson, Andrés F. Barrientos, V'ictor Pena, 2021, 2110.04852.

Bayesian Inferences on Uncertain Ranks and Orderings: Application to Ranking Players and Lineups

Andrés F. Barrientos, D. Dunson, Deborshee Sen, 2019, Bayesian Analysis.

Bayesian inferences on uncertain ranks and orderings

Andrés F. Barrientos, D. Dunson, Deborshee Sen, 2019 .

Diﬀerentially Private Methods for Validation Servers

Andrés F. Barrientos, Aaron R. Williams, J. Abowd, 2021 .

A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data

Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke, 2021, Journal of the American Statistical Association.

Differentially private methods for managing model uncertainty in linear regression models

Andrés F. Barrientos, V'ictor Pena, Andr'es F. Barrientos, 2021, 2109.03949.

A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses for Administrative Tax Data

Joshua Snoke, Claire McKay Bowen, Andrés F. Barrientos, 2021 .

Differentially Private Significance Tests for Regression Coefficients

Ashwin Machanavajjhala, Jerome P. Reiter, Yan Chen, 2017, Journal of Computational and Graphical Statistics.

Differentially Private Hypothesis Testing With the Subsampled and Aggregated Randomized Response Mechanism

Andrés F. Barrientos, V'ictor Pena, 2022, Statistica Sinica.

Differentially private methods for managing model uncertainty in linear regression models

Andrés F. Barrientos, V'ictor Pena, 2021, 2109.03949.

Providing access to confidential research data through synthesis and verification: An application to data on employees of the U.S. federal government

Ashwin Machanavajjhala, Jerome P. Reiter, John M. de Figueiredo, 2017, The Annals of Applied Statistics.

Dependent Bayesian nonparametric modeling of compositional data using random Bernstein polynomials

Andrés F. Barrientos, Alejandro Jara, Claudia Wehrhahn, 2021, Electronic Journal of Statistics.

Mixture representations and Bayesian nonparametric inference for likelihood ratio ordered distributions

David S. Matteson, Andrés F. Barrientos, Michael Jauch, 2021, 2110.04852.