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A maximin optimal approach for sampling designs in two-phase studies
Ruoyu Wang, Qihua Wang, Wang Miao
Data collection costs can vary widely across variables in data science tasks. Two-phase designs can be employed to save data collection costs. This paper considers the two-phase st…
A Moment-assisted Approach for Improving Subsampling-based MLE with Large-scale data
Miaomiao Su, Qihua Wang, Ruoyu Wang
The maximum likelihood estimation is computationally demanding for large datasets, particularly when the likelihood function includes integrals. Subsampling can reduce the computat…
A robust fusion-extraction procedure with summary statistics in the presence of biased sources
Ruoyu Wang, Qihua Wang, Wang Miao
Information from various data sources is increasingly available nowadays. However, some of the data sources may produce biased estimation due to commonly encountered biased samplin…
Distributed nonparametric regression imputation for missing response problems with large-scale data
Ruoyu Wang, Miaomiao Su, Qihua Wang
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 sa…
A Convex Programming Solution Based Debiased Estimator for Quantile with Missing Response and High-dimensional Covariables
Miaomiao Su, Qihua Wang
This paper is concerned with the estimating problem of response quantile with high dimensional covariates when response is missing at random. Some existing methods define root-n co…