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Hyokyoung Hong, Ph.D. - Publications

Affiliations: 
2008 University of Illinois, Urbana-Champaign, Urbana-Champaign, IL 
Area:
Statistics
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16 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Lee ER, Park S, Lee SK, Hong HG. Quantile forward regression for high-dimensional survival data. Lifetime Data Analysis. PMID 37393569 DOI: 10.1007/s10985-023-09603-w  0.471
2021 Fei Z, Zheng Q, Hong HG, Li Y. Inference for High-Dimensional Censored Quantile Regression. Journal of the American Statistical Association. 118: 898-912. PMID 37309513 DOI: 10.1080/01621459.2021.1957900  0.324
2020 Pijyan A, Zheng Q, Hong HG, Li Y. Consistent Estimation of Generalized Linear Models with High Dimensional Predictors via Stepwise Regression. Entropy (Basel, Switzerland). 22. PMID 33286734 DOI: 10.3390/E22090965  0.463
2019 Zheng Q, Hong HG, Li Y. Building Generalized Linear Models with Ultrahigh Dimensional Features: A Sequentially Conditional Approach. Biometrics. PMID 31350909 DOI: 10.1111/Biom.13122  0.392
2019 Hong HG, Zheng Q, Li Y. Forward regression for Cox models with high-dimensional covariates. Journal of Multivariate Analysis. 173: 268-290. PMID 31007300 DOI: 10.1016/J.Jmva.2019.02.011  0.452
2019 Lin H, Hong HG, Yang B, Liu W, Zhang Y, Fan G, Li Y. Nonparametric Time-Varying Coefficient Models for Panel Data Statistics in Biosciences. 11: 548-566. DOI: 10.1007/S12561-019-09248-0  0.319
2017 Kang J, Hong HG, Li YI. Partition-based ultrahigh-dimensional variable screening. Biometrika. 104: 785-800. PMID 29643546 DOI: 10.1093/biomet/asx052  0.411
2017 Hong HG, Chen X, Christiani DC, Li Y. Integrated powered density: Screening ultrahigh dimensional covariates with survival outcomes. Biometrics. PMID 29120498 DOI: 10.1111/Biom.12820  0.377
2016 Cho H, Hong HG, Kim MO. Efficient quantile marginal regression for longitudinal data with dropouts. Biostatistics (Oxford, England). PMID 26951723 DOI: 10.1093/biostatistics/kxw007  0.488
2016 Hong HG, Wang L, He X. A data-driven approach to conditional screening of high-dimensional variables Stat. 5: 200-212. DOI: 10.1002/STA4.115  0.344
2015 Hong H, Wang C, Lim YS, Douglas J. Efficient Models for Cognitive Diagnosis With Continuous and Mixed-Type Latent Variables. Applied Psychological Measurement. 39: 31-43. PMID 29880992 DOI: 10.1177/0146621614524981  0.326
2015 Hong H, Wang C, Lim YS, Douglas J. Efficient Models for Cognitive Diagnosis With Continuous and Mixed-Type Latent Variables Applied Psychological Measurement. 39: 31-43. DOI: 10.1177/0146621614524981  0.378
2013 He X, Wang L, Hong HG. Correction: Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data The Annals of Statistics. 41: 2699-2699. DOI: 10.1214/13-Aos1157  0.501
2013 He X, Wang L, Hong HG. Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data The Annals of Statistics. 41: 342-369. DOI: 10.1214/13-Aos1087  0.544
2013 Hong HG, Zhou J. A multi-index model for quantile regression with ordinal data Journal of Applied Statistics. 40: 1231-1245. DOI: 10.1080/02664763.2013.785489  0.537
2010 Hong HG, He X. Prediction of Functional Status for the Elderly Based on a New Ordinal Regression Model Journal of the American Statistical Association. 105: 930-941. DOI: 10.1198/Jasa.2010.Ap08631  0.517
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