Hyokyoung Hong, Ph.D.
Affiliations: | 2008 | University of Illinois, Urbana-Champaign, Urbana-Champaign, IL |
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Publications
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| Lee ER, Park S, Lee SK, et al. (2023) Quantile forward regression for high-dimensional survival data. Lifetime Data Analysis |
| Fei Z, Zheng Q, Hong HG, et al. (2021) Inference for High-Dimensional Censored Quantile Regression. Journal of the American Statistical Association. 118: 898-912 |
| Pijyan A, Zheng Q, Hong HG, et al. (2020) Consistent Estimation of Generalized Linear Models with High Dimensional Predictors via Stepwise Regression. Entropy (Basel, Switzerland). 22 |
| Zheng Q, Hong HG, Li Y. (2019) Building Generalized Linear Models with Ultrahigh Dimensional Features: A Sequentially Conditional Approach. Biometrics |
| Hong HG, Zheng Q, Li Y. (2019) Forward regression for Cox models with high-dimensional covariates. Journal of Multivariate Analysis. 173: 268-290 |
| Lin H, Hong HG, Yang B, et al. (2019) Nonparametric Time-Varying Coefficient Models for Panel Data Statistics in Biosciences. 11: 548-566 |
| Kang J, Hong HG, Li YI. (2017) Partition-based ultrahigh-dimensional variable screening. Biometrika. 104: 785-800 |
| Hong HG, Chen X, Christiani DC, et al. (2017) Integrated powered density: Screening ultrahigh dimensional covariates with survival outcomes. Biometrics |
| Cho H, Hong HG, Kim MO. (2016) Efficient quantile marginal regression for longitudinal data with dropouts. Biostatistics (Oxford, England) |
| Hong HG, Wang L, He X. (2016) A data-driven approach to conditional screening of high-dimensional variables Stat. 5: 200-212 |