Index of Page
· Mathematical Statistics and Decision Theory
· Applied Probability and Stochastic Processes
· Biostatistics, Survival Analysis, and Event-Time Analysis
· Recurrent Event Modeling and Analysis
· Reliability and Applications of Statistics in Engineering
· Simultaneous Inference and Multiple Testing
· Prediction Modeling and Prediction Machines
· Applications of Probability and Statistics in Finance
· High-Dimensional Inference and Machine Learning
· Foundational Issues in Statistics
· Applications of Mathematics, Probability and Statistics in Sports
· Applications of Statistics in the Sciences
Google Scholar List with Number of Citations
Some Math arXiv Preprints
§ “Game, Set, Match:” Double Delight Watching a Grand Slam Tennis Match. 2026 (with Dip Das and Yuexuan Wu). https://arxiv.org/abs/2603.02360
1. Baltazar-Aban, I. and Pena, E. (1995). Properties of Hazard-Based Residuals and Implications in Model Diagnostics. Journal of the American Statistical Association, 90, 185-197. Link
2. Pena, E. (1998). Smooth Goodness-of-Fit Tests for Composite Hypothesis in Hazard-Based Models. The Annals of Statistics, 26, 1935-1971. Link
3. Agustin, Ma. Zenia and Pena, E. (1999). Order Statistic Properties, Random Generation, and Goodness-of-Fit Testing for a Minimal Repair Model. Journal of the American Statistical Association, 94, 266-272. Link
4. Agustin, M. and Pena, E. (1999). A Dynamic Competing Risks Model. Probability in the Engineering and Informational Sciences, 13, 333-358. Link
5. Pena, E., Strawderman, R. and Hollander, M. (2001). Nonparametric Estimation with Recurrent Event Data. Journal of the American Statistical Association, 96, 1299-1315. Link
6. Hollander, M. and Pena, E. (2004). Nonparametric Methods in Reliability. Statistical Science, 19, 644-651. Link
7. Kvam, P. and Pena, E. (2005). Estimating Load-Sharing Properties in a Dynamic Reliability System. Journal of the American Statistical Association, 100, 262-272. Link
8. Dukic, V. and Pena, E. (2005). Variance Estimation in a Model with Gaussian Submodels. Journal of the American Statistical Association, 100, 296-309. Link
9. Pena, E. and Slate, E. (2006). Global Validation of Linear Model Assumptions. Journal of the American Statistical Association, 101, 341-354. Link
10.Pena, E., Slate, E. and Gonzalez, R. (2007). Semiparametric Inference for a General Class of Models for Recurrent Events. Journal of Statistical Planning and Inference, 137, 1727-1747. Link
11.Han, J., Slate, E. and Pena, E. (2007). Parametric latent class joint model for a longitudinal biomarker and recurrent events. Statistics in Medicine, 26, 5285-5302. Link
12.Stocker, R. and Pena, E. (2007). A General Class of Parametric Models for Recurrent Event Data. Technometrics, 49, 210-220. Link
13.Adekpedjou, A., Pena, E. and Quiton, J. (2010). Estimation and Efficiency with Recurrent Event Data under Informative Monitoring. Journal of Statistical Planning and Inference, 140, 597-615. Link
14.Pena, E., Habiger, J. and Wu, W. (2011). Power-Enhanced Family Wise Error and False Discovery Rate Controlling Multiple Decision Functions. The Annals of Statistics. 39, 556-583. Link
15.Habiger, J. and Pena, E. (2011). Randomized P-Values and Nonparametric Procedures in Multiple Testing. Journal of Nonparametric Statistics, 23, 583-604. Link
16.Adekpedjou, A. and Pena, E. (2012). Semiparametric estimation with recurrent event data under informative monitoring. Journal of Nonparametric Statistics, 24, 733-752. Link
17.Wu, W. and Pena, E. (2013). Bayes multiple decision functions. Electronic Journal of Statistics, 7, 1272-1300. Link
18.Taylor, L. and Pena, E. (2014). Nonparametric estimation with recurrent competing risks data. Lifetime Data Analysis, 20, 514-537. Link
19.Rahman, F., Lynch, J. and Pena, E. (2014). Nonparametric Bayes estimation of gap-time distribution with recurrent event data. Journal of Nonparametric Statistics, 26, 575-598. Link
20.Pena, E. (2016). Asymptotics for a General Class of Recurrent Event Models. Journal of Nonparametric Statistics, 28, 716-735. Link
21.Kindo, B., Wang, H. and Pena, E. (2016). Multinomial probit Bayesian additive regression trees. Stat, 5, 119-131. Link
22.Liu, P. and Pena, E. (2016). Sojourning with the Homogeneous Poisson Process. The American Statistician, 70, 413-423. Link
23.Pena, E. and Kim, T. (2019). Median confidence regions in a nonparametric model. Electronic Journal of Statistics, 13, 2348-2390. Link
24.Bottai, M., Kim, T., Lieberman, B., Luta, G., Pena, E. (2022). On Optimal Correlation-Based Prediction. The American Statistician, 76, 313-321. Link
25.Qiang, B. and Pena, E. (2023). Robust simultaneous estimation of location parameters. Statistics and Probability Letters, 193. Link
26. Tong, L., Liu, P., and Pena, E. (2025). Joint dynamic models and statistical inference for recurrent competing risks, longitudinal marker, and health status. Electronic Journal of Statistics, 19(2), 3068-3133. Link
27. Kim, T., Chase, P., Bottai, M., Doros, G., Giurcanu, M., Luta, G. And Pena, E. (2026). Maximum Agreement Linear Predictors. Electronic Journal of Statistics, 20, 2, 2892-2942. Link
28. Pena, E. (2026). Search for Truth through Data: NP decision processes, ROC functions, P-Functionals, knowledge updating, and sequential learning. SciEnggJ, 19, 02, 371-405. Link