大规模数据的扰动子抽样

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-01-01 DOI:10.5705/ss.202022.0020

Yujing Yao, Zhezhen Jin

引用次数: 0

摘要

在分析大规模数据时，子抽样方法和分治法很有吸引力，因为它们减轻了计算负担，同时保持了推断的有效性。在这种情况下，取样可以进行，也可以不进行更换。本文提出了一种基于独立同分布随机权重的扰动子抽样方法，用于分析大规模数据。通过建立估计量的渐近相合性和正态性，证明了基于优化凸目标函数的方法。该方法同时提供一致的点估计和方差估计。我们通过仿真研究和两个实际数据分析证明了所提出方法的有限样本性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.