Kernel regression utilizing heterogeneous datasets

Data analysis in modern scientific research and practice has shifted from analysing a single dataset to coupling several datasets. We propose study kernel regression method that can handle the challenge of heterogeneous populations. It greatly extends constrained [Dai, C.-S., & Shao, J. (2023). Kernel utilizing external information as constraints. Statistica Sinica, 33, press] requires homogeneous population different The asymptotic normality proposed estimators is established under some conditions simulation results are presented confirm our theory quantify improvements datasets with