Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data

Nonparametric regression imputation is commonly used in missing data analysis. However, it suffers from the curse of dimension. The problem can be alleviated by the explosive sample size in the era of big data, while the large-scale data size presents some challenges in the storage of data and the calculation of estimators. These challenges make the classical nonparametric regression imputation methods no longer applicable. This motivates us to develop two distributed nonparametric regression imputation methods. One is based on kernel …

analysis big big data challenges data data analysis distributed imputation kernel regression scale storage