# Statistical Inference after Kernel Ridge Regression Imputation under item nonresponse

arXiv: https://arxiv.org/abs/2102.00058 · HTML: https://mlsanity.com/paper/2102.00058/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 37 references that are in the map.
- First posted on arXiv 29 Jan 2021.

## Abstract (arXiv)

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 variance estimation. The proposed variance estimator is based on a linearization approach which employs the entropy method to estimate the density ratio. The root-n consistency of the imputation estimator is established when a Sobolev space is utilized in the kernel ridge regression imputation, which enables us to develop the proposed variance estimator. Synthetic data experiments are presented to confirm our theory.
