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大数据流的在线更新休伯稳健回归

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY
Statistics Pub Date : 2024-09-02 DOI:10.1080/02331888.2024.2398057
Chunbai Tao, Shanshan Wang
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引用次数: 0

摘要

大数据流已在多个行业引起极大关注。然而，高速流数据中巨大的数据量和异常值的存在给数据分析带来了巨大挑战。
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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Online updating Huber robust regression for big data streams
Big data streams have garnered significant attention in multiple industries. However, the immense volume and the presence of outliers in high-velocity streaming data pose great challenges to its an...
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来源期刊
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍： Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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