高效凸 PCA 与 Wasserstein GPCA 和排序数据的应用

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI:10.1080/10618600.2024.2402280

Steven Campbell, Ting-Kam Leonard Wong

引用次数: 0

摘要

Bigot 等人（2017）提出的凸PCA修改了欧几里得PCA，限制数据和主成分位于希尔伯特空间的给定凸子集中。这种设置...

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Efficient convex PCA with applications to Wasserstein GPCA and ranked data

Convex PCA, which was introduced in Bigot et al. (2017), modifies Euclidean PCA by restricting the data and the principal components to lie in a given convex subset of a Hilbert space. This setting...

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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.