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|a 10.1016/j.jmva.2021.104806
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|a eng
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1 |
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|a Li, Yehua
|e verfasserin
|4 aut
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| 245 |
1 |
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|a From multivariate to functional data analysis
|b fundamentals, recent developments, and emerging areas
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|c 2022
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 25.07.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a 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
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|a Journal Article
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|a Functional data analysis
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|a High-dimensional statistics
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|a Multi-level modeling
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| 650 |
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|a Spatial dependence
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|a Qiu, Yumou
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|a Xu, Yuhang
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