253 citations · 369 across the 7 of their papers we have counts for
7 papers
Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study
Seyoung Park, Eun Ryung Lee, Hyokyoung G. Hong
Health outcomes, such as body mass index and cholesterol levels, are known to be dependent on age and exhibit varying effects with their associated risk factors. In this paper, we…
Inference for High Dimensional Censored Quantile Regression
Zhe Fei, Qi Zheng, Hyokyoung G. Hong +1
With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper stati…
Estimation of time-varying reproduction numbers underlying epidemiological processes: a new statistical tool for the COVID-19 pandemic
Hyokyoung G. Hong, Yi Li
The coronavirus pandemic has rapidly evolved into an unprecedented crisis. The susceptible-infectious-removed (SIR) model and its variants have been used for modeling the pandemic.…
Covariance-Insured Screening
Kevin He, Jian Kang, Hyokyoung Grace Hong +5
Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors far greater than the sample size. In order to identify more novel biomarke…
Classification with Ultrahigh-Dimensional Features
Yanming Li, Hyokyoung Hong, Jian Kang +3
Although much progress has been made in classification with high-dimensional features \citep{Fan_Fan:2008, JGuo:2010, CaiSun:2014, PRXu:2014}, classification with ultrahigh-dimensi…
Conditional Screening for Ultra-high Dimensional Covariates with Survival Outcomes
Hyokyoung Grace Hong, Jian Kang, Yi Li
Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a…
Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
Xuming He, Lan Wang, Hyokyoung Grace Hong
We introduce a quantile-adaptive framework for nonlinear variable screening with high-dimensional heterogeneous data. This framework has two distinctive features: (1) it allows the…