Convergence rate for Nearest Neighbour matching: geometry of the domain and higher-order regularity
最近邻匹配的收敛率:支持域几何与高阶正则性
Estimating some mathematical expectations from partially observed data and in particular missing outcomes is a central problem encountered in numerous fields such as transfer learning, counterfactual analysis or causal inference. Matching estimators, estimators based on k-nearest neighbours, are widely used in this context. It is known that the variance of such estimators can converge to zero at a parametric rate, but their bias can have a slower rate when the dimension of…