| Variable selection for recurrent event data with broken adaptive ridge regression H Zhao, D Sun, G Li, J Sun Canadian Journal of Statistics 46 (3), 416-428, 2018 | 17 | 2018 |
| Do released prisoners’ perceptions of neighborhood condition affect reentry outcomes? L Liu, CA Visher, D Sun Criminal Justice Policy Review 32 (7), 764-789, 2021 | 14 | 2021 |
| Inference on an adaptive accelerated life test with application to smart-grid data-acquisition-devices L Shen, D Sun, Z Ye, X Zhao Journal of Quality Technology 49 (3), 191-212, 2017 | 13 | 2017 |
| An early adverse experience goes a long, criminogenic, gendered way: The nexus of early adversities, adult offending, and gender L Liu, SL Miller, J Qiu, D Sun Women & Criminal Justice 31 (1), 24-39, 2021 | 12 | 2021 |
| Regression analysis of asynchronous longitudinal data with informative observation processes D Sun, H Zhao, J Sun Computational Statistics & Data Analysis 157, 107161, 2021 | 7 | 2021 |
| Do both petty and serious female offenders have shorter incarcerations than their male counterparts? Testing the universality of chivalrous treatment L Liu, R Bachman, J Qiu, D Sun Women & Criminal Justice 33 (4), 310-324, 2023 | 6 | 2023 |
| Violent victimization during reentry: Prevalence, triggers, and impact on mental health L Liu, TJ Mowen, CA Visher, D Sun Justice Quarterly 40 (4), 534-558, 2023 | 6 | 2023 |
| When post-incarcerated individuals return to high-risk neighborhoods: Staying out of trouble, social withdrawal, and mental health L Liu, CA Visher, DJ O’Connell, D Sun Crime & Delinquency 68 (12), 2253-2273, 2022 | 4 | 2022 |
| Simultaneous estimation and variable selection for incomplete event history studies H Zhao, D Sun, G Li, J Sun Journal of Multivariate Analysis 171, 350-361, 2019 | 4 | 2019 |
| Inference of a time-varying coefficient regression model for multivariate panel count data Y Guo, D Sun, J Sun Journal of Multivariate Analysis 192, 105047, 2022 | 3 | 2022 |
| Supplement to “A New Robust Approach for Regression Analysis of Panel Count Data with Time-varying Covariates” D SUN, Y GUO, Y LI, W TU, J SUN | 1 | 2024 |
| Regression analysis of general mixed recurrent event data R Sun, D Sun, L Zhu, J Sun Lifetime Data Analysis 29 (4), 807-822, 2023 | 1 | 2023 |
| Kernel meets sieve: transformed hazards models with sparse longitudinal covariates D Sun, Z Sun, X Zhao, H Cao arXiv preprint arXiv:2308.15549, 2023 | 1 | 2023 |
| REGRESSION ANALYSIS OF PANEL COUNT DATA WITH BOTH TIME-DEPENDENT COVARIATES AND TIME-VARYING EFFECTS. Y Guo, D Sun, J Sun Statistica Sinica 33 (2), 2023 | 1 | 2023 |
| A robust approach for regression analysis of panel count data with time-varying covariates D Sun, Y Guo, Y Li, W Tu, J Sun Bernoulli 30 (4), 3251-3275, 2024 | | 2024 |
| A flexible time-varying coefficient rate model for panel count data D Sun, Y Guo, Y Li, J Sun, W Tu Lifetime Data Analysis, 1-21, 2024 | | 2024 |
| Semiparametric analysis of complex longitudinal data D Sun University of Missouri--Columbia, 2020 | | 2020 |
JIANGUO SUNUniversity of Missouri在 missouri.edu 的电子邮件经过验证
