首页|From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

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  • NSTL
  • Elsevier
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 Journal of Multivariate Analysis. 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. (C) 2021 Elsevier Inc. All rights reserved.

Functional data analysisHigh-dimensional statisticsMulti-level modelingSpatial dependencePRINCIPAL COMPONENT ANALYSISVARYING COEFFICIENT MODELSSPATIOTEMPORAL POINT-PROCESSESGENERALIZED LINEAR-MODELSLIKELIHOOD RATIO TESTSVARIABLE SELECTIONSPLINE MODELSSPARSEREGRESSIONSTATISTICS

Li, Yehua、Qiu, Yumou、Xu, Yuhang

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Univ Calif Riverside

Iowa State Univ

Bowling Green State Univ

2022

10.1016/j.jmva.2021.104806

Journal of Multivariate Analysis

Journal of Multivariate Analysis

SCI
ISSN：0047-259X
年,卷(期)：2022.188
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