A review of distributed statistical inference

Yuan Gao, Weidong Liu, Hansheng Wang, Xiaozhou Wang, Yibo Yan and Riquan Zhang

Statistical Theory and Related Fields, 2022, vol. 6, issue 2, 89-99

Abstract: The rapid emergence of massive datasets in various fields poses a serious challenge to traditional statistical methods. Meanwhile, it provides opportunities for researchers to develop novel algorithms. Inspired by the idea of divide-and-conquer, various distributed frameworks for statistical estimation and inference have been proposed. They were developed to deal with large-scale statistical optimization problems. This paper aims to provide a comprehensive review for related literature. It includes parametric models, nonparametric models, and other frequently used models. Their key ideas and theoretical properties are summarized. The trade-off between communication cost and estimate precision together with other concerns is discussed.

Date: 2022
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DOI: 10.1080/24754269.2021.1974158

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