| On computing the distribution function for the Poisson binomial distribution Y Hong Computational Statistics & Data Analysis 59, 41-51, 2013 | 404* | 2013 |
| Reliability meets big data: opportunities and challenges WQ Meeker, Y Hong Quality Engineering 26 (1), 102-116, 2014 | 264 | 2014 |
| Prediction of remaining life of power transformers based on left truncated and right censored lifetime data Y Hong, WQ Meeker, JD McCalley The Annals of Applied Statistics 3 (2), 857-879, 2009 | 195 | 2009 |
| Copula-based reliability analysis of degrading systems with dependent failures G Fang, R Pan, Y Hong Reliability Engineering & System Safety 193, 106618, 2020 | 129 | 2020 |
| Using accelerated life tests results to predict product field reliability WQ Meeker, LA Escobar, Y Hong Technometrics 51 (2), 146-161, 2009 | 122 | 2009 |
| Statistical methods for degradation data with dynamic covariates information and an application to outdoor weathering data Y Hong, Y Duan, WQ Meeker, DL Stanley, X Gu Technometrics 57 (2), 180-193, 2015 | 96 | 2015 |
| Field-Failure Predictions Based on Failure-time Data with Dynamic Covariate Information Y Hong, WQ Meeker Technometrics 55 (2), 135-149, 2013 | 87 | 2013 |
| Big data and reliability applications: The complexity dimension Y Hong, M Zhang, WQ Meeker Journal of Quality Technology 50 (2), 135-149, 2018 | 83 | 2018 |
| Profile monitoring based quality control method for fused deposition modeling process K He, Q Zhang, Y Hong Journal of Intelligent Manufacturing 2018, 1-12, 2018 | 79 | 2018 |
| Reliability analysis of repairable systems with dependent component failures under partially perfect repair Q Yang, N Zhang, Y Hong IEEE Transactions on Reliability 62 (2), 490-498, 2013 | 75 | 2013 |
| Nonlinear general path models for degradation data with dynamic covariates Z Xu, Y Hong, R Jin Applied Stochastic Models in Business and Industry 32 (2), 153-167, 2016 | 72 | 2016 |
| Field-failure and warranty prediction based on auxiliary use-rate information Y Hong, WQ Meeker Technometrics 52 (2), 148-159, 2010 | 68 | 2010 |
| How do heterogeneities in operating environments affect field failure predictions and test planning? ZS Ye, Y Hong, Y Xie The Annals of Applied Statistics, 2249-2271, 2013 | 63 | 2013 |
| Accurate reliability inference based on Wiener process with random effects for degradation data X Wang, BX Wang, PH Jiang, Y Hong Reliability Engineering & System Safety 193, 106631, 2020 | 46 | 2020 |
| Degradation data analysis based on gamma process with random effects X Wang, BX Wang, Y Hong, PH Jiang European Journal of Operational Research 292 (3), 1200-1208, 2021 | 45 | 2021 |
| General path models for degradation data with multiple characteristics and covariates L Lu, B Wang, Y Hong, Z Ye Technometrics 63 (3), 354-369, 2021 | 43 | 2021 |
| Applications of the fractional-random-weight bootstrap L Xu, C Gotwalt, Y Hong, CB King, WQ Meeker The American Statistician 74 (4), 345-358, 2020 | 42 | 2020 |
| ADAPT-2: a randomized clinical trial to reduce intraoperative EEG suppression in older surgical patients undergoing major noncardiac surgery CJ Tang, Z Jin, LP Sands, D Pleasants, S Tabatabai, Y Hong, JM Leung Anesthesia & Analgesia 131 (4), 1228-1236, 2020 | 41 | 2020 |
| Fault diagnosis of FDM process based on support vector machine (SVM) H Hu, K He, T Zhong, Y Hong Rapid Prototyping Journal 26 (2), 330-348, 2020 | 41 | 2020 |
| A tool for evaluating time-varying-stress accelerated life test plans with log-location-scale distributions Y Hong, H Ma, WQ Meeker IEEE Transactions on Reliability 59 (4), 620-627, 2010 | 40 | 2010 |
William Q. MeekerDistinguished Professor of Statistics at Iowa State UniversityVerified email at iastate.edu
