Publication List

See Google Scholar for a More Up-to-Date List

  1. Sun, Q., Ye,. Z. and Hong, Y. (2019), Statistical Modeling of Multivariate Destructive Degradation Tests with Blocking, Technometrics, tentatively accepted.
  2. Fang, G., Pan, R., and Hong, Y. (2019), A Copula-based Reliability Analysis for Degrading System with Accelerated Degradation Processes, Reliability Engineering & System Safety, in press.
  3. Xie, Y., Xu, L., Li, J., Deng, X., Hong, Y., Kolivras, K. N., and David N. Gaines (2019), Spatial Variable Selection via Adaptive Elastic Net and An Application to Virginia Lyme Disease Case Data, Journal of the American Statistical Association, in press.
  4. Ding, Y., Yang, Q., King, C., and Hong, Y. (2019), A General Accelerated Destructive Degradation Testing Model for Reliability Analysis, IEEE Transactions on Reliability, in press.
  5. Cameron, K., Anwar, A., Cheng, Y., Xu, L., Li, B., Ananth, U., Bernard, J., Jearls, C., Lux, T., Hong, Y., Watson, L., and Butt, A. (2019), MOANA: Modeling and Analyzing HPC I/O Variability, IEEE Transactions on Parallel and Distributed Systems, in press.
  6. Stevens, L. K., Kolivras, K. N., \textbf{Hong, Y.}, Thomas, V. A., Campbell, J. B., and Prisley, S. P. (2019), Future Lyme Disease Risk in the Southeastern United States Based on Projected Land Cover, Geospatial Health, Vol. 14, pp. 153-162.
  7. Yuan, M., Tang, C., Hong, Y., and Yang, J. (2018), Disentangling and Assessing Uncertainties in Multiperiod Corporate Default Risk Predictions, The Annals of Applied Statistics, in press.
  8. Lee, I., Hong, Y., Tseng, S. T., and Dasgupta, T. (2018), Sequential Test Planning for Polymer Composites, Technometrics, in press.
  9. Hong, Y., Zhang, M., and Meeker, W. Q., (2018), Big Data and Reliability Applications: The Complexity Dimension, Journal of Quality Technology, Vol. 50, pp. 135-149.
  10. Zhang, M., Hong, Y., and Balakrishnan, N. (2018), The Generalized Poisson Binomial Distribution and the Computing of Its Distribution Functions, Journal of Statistical Computation and Simulation, in press.
  11. He, K., Zhang, Q., and Hong, Y. (2018), Profile Monitoring based Quality Control Method for Fused Deposition Modeling Process, Journal of Intelligent Manufacturing, in press.
  12. Sands, L. P., Xie, Y., Pruchno, R., Hong, Y., and Heid, A. (2018), Older Adults' Health Care Utilization a Year After Experiencing Fear or Distress from Hurricane Sandy, Disaster Medicine and Public Health Preparedness , in press.
  13. Xie, Y., King, C., Hong, Y., and Yang, Q. (2018), Semiparametric Models for Accelerated Destructive Degradation Test Data Analysis, Technometrics, in press.
  14. Wang, X., Ye, Z., Hong, Y., and Tang, L. C. (2018), Analysis of Field Return Data with Failed-But-Not-Reported Events, Technometrics, Vol. 60, pp. 90-100.
  15. King, C., Hong, Y., Xie, Y., Van Mullekom, J. H., DeHart, S. P., and DeFeo, P. A. (2018), A Comparison of Traditional and Maximum Likelihood Approaches to Estimating Thermal Index for Polymeric Materials, Journal of Quality Technology, Vol. 50, pp. 117-129.
  16. Yuan, M.}, Hong, Y., Escobar, L. A., and Meeker, W. Q. (2018), Tolerance Interval for (Log) Location-Scale Family of Distributions, Quality Technology and Quantitative Management , Vol. 15, pp. 374-392.
  17. Duan, Y., Hong, Y., Meeker, W. Q., Stanley, D. L., and Gu, X. (2017), Photodegradation modeling based on laboratory accelerated test data and predictions under outdoor weathering for polymeric materials, The Annals of Applied Statistics , Vol. 11, pp. 2052-2079.
  18. Yang, Q., Hong, Y., Zhang, N., and Li, J. (2017), A Copula-Based Trend-Renewal Process Model for Analysis of Repairable Systems With Multitype Failures, IEEE Transactions on Reliability , Vol. 66, pp. 590-602.
  19. Liu, X., Liu, C., and Hong, Y. (2017), Analysis of multiple tank car releases in train accidents, Accident Analysis and Prevention, Vol. 107, pp. 164-172.
  20. Xu, Z., Hong, Y., Meeker, W. Q., Osborn, B. E., and Illouz, K. (2017), A Multi-level Trend-renewal Process for Modeling Systems with Recurrence Data, Technometrics, Vol. 59, pp. 225-236.
  21. Xie, Y., Hong, Y., Escobar, L. A., and Meeker, W. Q. (2017), A General Algorithm for Computing Simultaneous Prediction Intervals for the (Log)-Location-Scale Family of Distributions, Journal of Statistical Computation and Simulation, Vol. 87, pp. 1559-1576.
  22. King, C., Hong, Y., and Meeker, W. Q. (2017), Product Component Genealogy Modeling and Field-Failure Prediction, Quality and Reliability Engineering International, Vol. 33, pp. 135-148.
  23. Khosrowpour, A., Xie, Y., Taylor, J. E., and Hong, Y. (2016), One Size Does Not Fit All: Establishing the Need for Targeted Eco-Feedback, Applied Energy, Vol. 184, pp. 523-530.
  24. Bedair, K. Hong, Y., Li, J., and Al-Khalidi, H. R. (2016), Multivariate Frailty Models for Multi-type Recurrent Event Data and an Application to Cancer Prevention Trial, Computational Statistics and Data Analysis, Vol. 101, pp. 161-173.
  25. King, C., Hong, Y., DeHart, S. P., DeFeo, P. A., and Pan, R. (2016), Planning Fatigue Tests for Polymer Composites, Journal of Quality Technology, Vol. 28, pp. 227-245.
  26. Thapa, R., Burkhart, H. E., Hong, Y., and Li, J. (2016), Modeling Loblolly Pine (Pinus taeda L.) Clustered Survival Time with Time-dependent Covariates and Shared Frailties, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 21, pp. 92-110.
  27. Xu, Z., Hong, Y., and Jin, R. (2016), Nonlinear General Path Models for Degradation Data with Dynamic Covariates, Applied Stochastic Models in Business and Industry, Vol. 32, pp. 153-167.
  28. Rubio, F. J. and Hong, Y. (2016), Survival and Lifetime Data Analysis with a Flexible Class of Distributions, Journal of Applied Statistics, Vol. 43, pp. 1794-1813.
  29. Li, J., Hong, Y., Thapa, R., and Burkhart, H. E. (2015), Survival Analysis of Loblolly Pine Trees with Spatially Correlated Random Effects, Journal of the American Statistical Association, Vol. 110, pp. 486-502.
  30. Liu, X. and Hong, Y. (2015), Modeling Correlated Railroad Crude Oil Tank Car Releases Using a Generalized Binomial Model, Accident Analysis and Prevention, Vol. 84, pp. 20-26.
  31. Hong, Y., Duan, Y., Meeker, W. Q., Stanley, D. L., and Gu, X. (2015), Statistical Methods for Degradation Data with Dynamic Covariates Information and an Application to Outdoor Weathering Data, Technometrics, Vol. 57, pp. 180-193.
  32. Hong, Y., King, C., Zhang, Y., and Meeker, W. Q. (2015), Bayesian Life Test Planning for Log-Location-Scale Family of Distributions, Journal of Quality Technology, Vol. 47, pp. 336-350.
  33. Seukep, S. E., Kolivras, K. N., Hong, Y., Li, J., Prisley, S. P., Campbell, J. B., Gaines, D. N., and Dymond, R. L. (2015), An Examination of the Demographic and Environmental Variables Correlated with Lyme Disease Emergence in Virginia, EcoHealth, Vol. 12, pp. 634-44.
  34. Hong, Y., Li, M., and Osborn, B. (2015), System Unavailability and Cost Analysis Based on Window-Observed Recurrent Event Data, Applied Stochastic Models in Business and Industry, Vol. 31, pp. 122-136.
  35. Xu, Z., Hong, Y., and Meeker, W. Q. (2015), Assessing Risk of a Serious Failure Mode Based on Limited Field Data, IEEE Transactions on Reliability, Vol. 64, pp. 51-62.
  36. Li, J., Kolivras, K. N., Hong, Y., Duan, Y., Seukep, S. E., Prisley, S. P., Campbell, J. B., and Gaines, D. N. (2014), Spatial and Temporal Emergence Pattern of Lyme Disease in Virginia, The American Journal of Tropical Medicine and Hygiene, Vol. 91, pp. 1166-1172.
  37. Hong, Y. and Meeker, W. Q. (2014), Confidence Interval Procedures for System Reliability and Applications to Competing Risks Models, Lifetime Data Analysis, Vol. 20, pp. 161-184.
  38. Meeker, W. Q. and Hong, Y. (2014), Reliability Meets Big Data: Opportunities and Challenges (with discussion), Quality Engineering, Vol. 26, pp. 102-116.
  39. Ye, Z., Hong, Y., and Xie, Y. (2013), How do Heterogeneities in Operational Environments Affect Field Failures?, The Annals of Applied Statistics, Vol. 7, pp. 2249-2271.
  40. Hong, Y. and Meeker, W. Q. (2013), Field-Failure Predictions Based on Failure-time Data with Dynamic Covariate Information, Technometrics, Vol. 55, pp. 135-149.
  41. Yang, Q., Zhang, N., and Hong, Y. (2013), Statistical Reliability Analysis of Repairable Systems with Dependent Component Failures under Partially Perfect Repair Assumption, IEEE Transactions on Reliability, Vol. 62, pp. 490-498.
  42. Hong, Y. (2013), On Computing the Distribution Function for the Poisson Binomial Distribution, Computational Statistics and Data Analysis, Vol. 59, pp. 41-51.
  43. Yang, Q., Hong, Y., Chen, Y., and Shi, J. (2012), Failure Profile Analysis of a Single Repairable System Using Trend-renewal Process, IEEE Transactions on Reliability, Vol. 61, pp. 180-191.
  44. Al-Khalidi, H. R., Hong, Y., Fleming, T. R., and Therneau, T. (2011), Insights on the Robust Standard Error Under Recurrent Events Model, Biometrics, Vol. 67, pp. 1564-1572.
  45. Hong, Y. and Meeker, W. Q. (2011), The Importance of Identifying Different Components of a Mixture Distribution in the Prediction of Field Returns. Applied Stochastic Models in Business and Industry, Vol. 27, pp. 280-289.
  46. Hong, Y., Ma, H., and Meeker, W. Q. (2010), A Tool for Evaluating Time-Varying-Stress Accelerated Life Test Plans with Log-Location-Scale Distributions. IEEE Transactions on Reliability, Vol. 59, pp. 620-627.
  47. Hong, Y. and Meeker, W. Q. (2010), Field-Failure and Warranty Prediction Using Auxiliary Use-rate Data. Technometrics, Vol. 52, pp. 148-159.
  48. Hong, Y., Escobar, L. A., and Meeker, W. Q. (2010), Coverage Probabilities of Simultaneous Confidence Bands and Regions for Log-Location-Scale Distributions, Statistic & Probability Letters, Vol. 80, pp. 733-738.
  49. Escobar, L. A., Hong, Y., and Meeker, W. Q. (2009), Simultaneous Confidence Bands and Regions for Log-Location-Scale Distributions with Censored Data, Journal of Statistical Planning and Inference, Vol. 139, No. 9, pp. 3231-3245.
  50. Hong, Y., Meeker, W. Q., and McCalley, J. D. (2009), Prediction Intervals for Remaining Life of Power Transformers Based on Left Truncated and Right Censored Lifetime Data, The Annals of Applied Statistics, Vol. 3, No. 2, pp. 857-879.
  51. Meeker, W. Q., Escobar, L. A., and Hong, Y. (2009), Using Accelerated Life Tests Results to Predict Product Field Reliability, Technometrics, Vol. 51, No. 2, pp. 146-161.
  52. Hong, Y., Meeker, W. Q., and Escobar, L. A. (2008), The Relationship Between Confidence Intervals for Failure Probabilities and Life Time Quantiles, IEEE Transactions on Reliability, Vol. 57, No. 2, pp. 260-266.
  53. Hong, Y., Meeker, W. Q., and Escobar, L. A. (2008), Avoiding Problems with Normal Approximation Confidence Intervals for Probabilities, Technometrics, Vol. 50, No. 1, pp. 64-68.
  54. Lu, L., Lee, I., and Hong, Y. (2018), Bayesian Sequential Design Based on Dual Objectives for Accelerated Life Tests, Book chapter for "Statistical Quality Technologies: Theory and Practice" by Springer, tentatively accepted.
  55. Lux, T. C. H., Watson, L., Chang, T. H., Bernard, J., Li, B., Yu, X., Xu, L., Back, G., Butt, A. R., Cameron, K. W., Yao, D., and Hong, Y. (2018), Novel meshes for multivariate interpolation and approximation. Association for Computing Machinery, ACM Southeast Conference.
  56. Chang, T. H., Watson, L. T., Lux, T. C.H., Li, B., Xu, L., Butt, A. R., Cameron, K. W., and Hong, Y. (2018), A Polynomial Time Algorithm for Multivariate Interpolation in Arbitrary Dimension via the Delaunay Triangulation, ACM SE '18: ACM Southeast Conference, accepted.
  57. Chang, T. H., Watson, L. T., Lux, T. C. H. Raghvendra, S., Li, B., Xu, L., Butt, A. R., Cameron, K. W., and Hong. Y., (2018). Computing the umbrella neighbourhood of a vertex in the Delaunay triangulation and a single Voronoi cell in arbitrary dimension. In SoutheastCon 2018. IEEE, St. Petersburg, FL, USA, pp. 1-8. DOI: 10.1109/SECON.2018.8479003
  58. Chang, T. H., Watson, L. T., Lux, T. C. H., Xu, L., Back, G., Butt, A. R., Cameron, K. W. and Hong, Y. (2018), Predicting System Performance By Interpolation Using A High-Dimensional Delaunay Triangulation, SpringSim-HPC, 2018, accepted.
  59. Lux, T. C. H., Watson, L., Chang, T. H., Li, B., Bernard, J., Xu, L., Back, G., Butt, A. R., Cameron, K. W. and Hong, Y. (2018), Predictive Modeling Of I/O Characteristics in High Performance Computing Systems, SpringSim-HPC, 2018, accepted.
  60. Lux, T. C. H., Watson, L., Bernard, J., Chang, T. H., Li, B., Xu, L., Back, G., Butt, A. R., Cameron, K. W. and Hong, Y. (2018), Nonparametric Distribution Models for Predicting and Managing Computational Performance Variability, IEEE SoutheastCon, 2018, accepted.
  61. Lux, T. C. H., Watson, L., Chang, T. H., Bernard, J., Li, B., Xu, L., Back, G., Butt, A. R., Cameron, K. W. and Hong, Y. (2017), A first look: Using linux containers for deceptive honeypots. Association for Computing Machinery, Workshop on Assurable and Usable Security Configuration (SafeConfig).
  62. Fang, G., Pang, R., and Hong, Y. (2018), A Copula-based Multivariate Degradation Analysis for Reliability Prediction, Reliability and Maintainability Symposium (RAMS), 2018 Annual, in press.
  63. King, C. B., Xu, Z., Lee, I., and Hong, Y. (2018), Reliability Analysis of Polymeric Materials, Wiley StatsRef: Statistics Reference Online , in press.
  64. Xie, Y., Jin, Z., Hong, Y., and Van Mullekom, J. H. (2017), Statistical Methods for Thermal Index Estimation Based on Accelerated Destructive Degradation Test Data, Chapter 12 for "Statistical Modelling for Degradation Data," Springer.
  65. Jin, Z., Xie, Y., Hong, Y., and Van Mullekom, J. H. (2017), ADDT: An R Package for Analysis of Accelerated Destructive Degradation Test Data, Chapter 14 for "Statistical Modelling for Degradation Data," Springer.
  66. Zhang, Y., Liao, H, and Hong, Y. (2015), Planning Accelerated Destructive Degradation Tests with Initiation Time, Reliability and Maintainability Symposium (RAMS), 2015 Annual.
  67. Meeker, W. Q., Hong, Y., and Escobar, L. A. (2011), Degradation Models and Data Analyses, Encyclopedia of Statistical Sciences.
  68. Meeker, W. Q., Hong, Y., and Escobar, L. A. (2011), The Failure-based Paradigm, The Wiley Encyclopedia of Operations Research and Management Science.
  69. Meeker, W. Q., Hong, Y., and Escobar, L. A. (2011), The Condition-based Paradigm, The Wiley Encyclopedia of Operations Research and Management Science.
  70. Hong, Y. and Meeker, W.Q. (2010), Field Failure Prediction Using Dynamic Environmental Data. Chapter 16 in Mathematical and Statistical Methods in Reliability. Applications to Medicine, Finance and Quality Control (Eds. N. Balakrishnan, M. Nikulin, V. Rykov), Birkhauser: Boston.
  71. McCalley, J. D., Honavar, V., Ryan, S. M., Meeker, W. Q., Qiao, D., Roberts, R. A., Li, Y., Pathak, J., Ye, M., Hong, Y. (2007), Integrated Decision Algorithms for Auto-steered Electric Transmission System Asset Management, International Conference on Computational Science (1), pp. 1066-1073.
  72. Hong, Y., Liao, H., Yashchin, E., and Tsung, F. (2018), Editor's Notes on Special Issue on "Reliability and Maintenance Modeling with Big Data", Journal of Quality Technology, Vol. 50, pp. 133-134.
  73. Xu, L., and Hong, Y. (2017), Book review for "Functional Shape Analysis", Journal of Quality Technology, Vol. 49, pp. 419-420.
  74. Meeker, W. Q. and Hong, Y. (2014), Rejoinder for "Reliability Meets Big Data: Opportunities and Challenges," Quality Engineering , Vol. 26, pp. 127-129.
  75. Hong, Y. and King, C. (2014), Invited discussion on "EM-based Likelihood Inference for Some Lifetime Distributions Based on Left Truncated and Right Censored Data and Associated Model Discrimination" by N. Balakrishnan and D. Mitra, South African Statistical Journal , Vol. 48, 181-182.
  76. Hong, Y. and Xu, Z. (2014), Invited discussion on "Methods For Planning Accelerated Repeated Measures Degradation Tests" by B. Weaver and W. Q. Meeker, Applied Stochastic Models in Business and Industry , Vol. 30, pp. 672-673.
  77. Sands, L. P., Xie, Y., Yuan, M., and Hong, Y. (2015), Change In Reports of Unmet Need for Help with ADL or Mobility Disabilities Across Three Years, The Gerontologist , Vol. 55(Suppl 2), pp. 722-723.