3 papers
stat.ME2025
Multi-source Learning for Target Population by High-dimensional Calibration
Haoxiang Zhan, Jae Kwang Kim, Yumou Qiu
Multi-source learning is an emerging area of research in statistics, where information from multiple datasets with heterogeneous distributions is combined to estimate the parameter…
stat.ME2025
A General Approach for Calibration Weighting under Missing at Random
Yonghyun Kwon, Jae Kwang Kim, Yumou Qiu
We propose a unified class of calibration weighting methods based on weighted generalized entropy to handle missing at random (MAR) data with improved stability and efficiency. The…
stat.ME2024
Generalized entropy calibration for analyzing voluntary survey data
Yonghyun Kwon, Jae Kwang Kim, Yumou Qiu
Statistical analysis of voluntary survey data is an important area of research in survey sampling. We consider a unified approach to voluntary survey data analysis under the assump…