大规模数据的扰动子抽样

IF 1.5 3区 数学 Q2 STATISTICS & PROBABILITY
Yujing Yao, Zhezhen Jin
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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。
A Perturbation Subsampling for Large Scale Data
Subsampling
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来源期刊
Statistica Sinica
Statistica Sinica 数学-统计学与概率论
CiteScore
2.10
自引率
0.00%
发文量
82
审稿时长
10.5 months
期刊介绍: Statistica Sinica aims to meet the needs of statisticians in a rapidly changing world. It provides a forum for the publication of innovative work of high quality in all areas of statistics, including theory, methodology and applications. The journal encourages the development and principled use of statistical methodology that is relevant for society, science and technology.
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