非高斯数据的主变量分析

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-06-13 DOI:10.1080/10618600.2024.2367098

Dylan Clark-Boucher, Jeffrey W. Miller

引用次数: 0

摘要

主变量分析（PVA）是一种选择变量子集的技术，可以尽可能多地捕捉数据集中的信息。现有的主变量分析方法基于...

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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Principal variables analysis for non-Gaussian data

Principal variables analysis (PVA) is a technique for selecting a subset of variables that capture as much of the information in a dataset as possible. Existing approaches for PVA are based on the ...

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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.