Li Yehua, Qiu Yumou, Xu Yuhang
University of California - Riverside, Riverside, CA 92521, USA.
Iowa State University, Ames, IA 50011, USA.
J Multivar Anal. 2022 Mar;188. doi: 10.1016/j.jmva.2021.104806. Epub 2021 Aug 18.
Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for . We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. We also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.
功能数据分析(FDA)是统计学的一个分支,用于对存在于函数空间中的无限维随机向量进行建模,已成为一个主要的研究领域。我们回顾了功能数据分析的一些基本概念、它们的起源以及与多元分析的联系,还有它最近的一些发展,包括多层次功能数据分析、高维功能回归和相依功能数据分析。我们还讨论了这些新方法发展对遗传学、植物科学、可穿戴设备数据分析、图像数据分析和商业分析的影响。提供了两个实际数据示例来推动我们的讨论。