Optimal Subsampling for Functional Quasi-Mode Regression with Big Data

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI:10.1080/10618600.2024.2402279

Tao Wang

引用次数: 0

Abstract

We propose investigating optimal subsampling for functional regression with massive datasets based on the mode value, which is referred to as functional quasi-mode regression, to reduce data volume...

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大数据功能准模式回归的最佳子采样

我们建议研究基于模态值的海量数据集函数回归的最优子采样，即函数准模态回归，以减少数据量...

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.