most citedStatistical Inference after Kernel Ridge Regression Imputation under item nonresponse

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ME2023

Robust propensity score weighting estimation under missing at random

Hengfang Wang, Jae Kwang Kim, Jeongseop Han +1

Missing data is frequently encountered in many areas of statistics. Propensity score weighting is a popular method for handling missing data. The propensity score method employs a…

stat.ML2023

Transductive Matrix Completion with Calibration for Multi-Task Learning

Hengfang Wang, Yasi Zhang, Xiaojun Mao +1

Multi-task learning has attracted much attention due to growing multi-purpose research with multiple related data sources. Moreover, transduction with matrix completion is a useful…

stat.ME2021

Statistical inference using Regularized M-estimation in the reproducing kernel Hilbert space for handling missing data

Hengfang Wang, Jae Kwang Kim

Imputation and propensity score weighting are two popular techniques for handling missing data. We address these problems using the regularized M-estimation techniques in the repro…

stat.ME2021

Information projection approach to propensity score estimation for handling selection bias under missing at random

Hengfang Wang, Jae Kwang Kim

Propensity score weighting is widely used to improve the representativeness and correct the selection bias in the voluntary sample. The propensity score is often developed using a…

stat.ME2021★ 3 cited

Statistical Inference after Kernel Ridge Regression Imputation under item nonresponse

Hengfang Wang, Jae-Kwang Kim

Imputation is a popular technique for handling missing data. We consider a nonparametric approach to imputation using the kernel ridge regression technique and propose consistent v…