Regional quantile regression for multiple responses
S Park, H Kim, ER Lee - Computational Statistics & Data Analysis, 2023 - Elsevier
In this article, we study high-dimensional multiple response quantile regression model for an
interval of quantile levels, in which a common set of covariates is used to analyze multiple …
interval of quantile levels, in which a common set of covariates is used to analyze multiple …
Quantile forward regression for high-dimensional survival data
Despite the urgent need for an effective prediction model tailored to individual interests,
existing models have mainly been developed for the mean outcome, targeting average …
existing models have mainly been developed for the mean outcome, targeting average …
Varying‐coefficients for regional quantile via KNN‐based LASSO with applications to health outcome study
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 …
dependent on age and exhibit varying effects with their associated risk factors. In this paper …
Penalized kernel quantile regression for varying coefficient models
In nonparametric models, numerous penalization methods using a nonparametric series
estimator have been developed for model selection and estimation. However, a penalization …
estimator have been developed for model selection and estimation. However, a penalization …