A distribution-free method for change point detection in non-sparse high dimensional data

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-06-12 DOI:10.1080/10618600.2024.2365733

Reza Drikvandi, Reza Modarres

引用次数: 0

Abstract

We propose a distribution-free distance-based method for high dimensional change points that can address challenging situations when the sample size is very small compared to the dimension as in th...

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在非稀疏高维数据中检测变化点的无分布方法

我们针对高维变化点提出了一种基于无分布距离的方法，该方法可以解决样本量与维度相比非常小的挑战性情况，例如在...

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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.