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WileySTAT-V1.pdf
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2021-11-04
Type
Book ChapterAuthors
Genton, Marc G.
Sun, Ying

KAUST Department
Statistics ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2020-11-04Embargo End Date
2021-11-04Permanent link to this record
http://hdl.handle.net/10754/667759
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This article reviews tools to visualize functional data, that is, curves, surfaces/images, and trajectories. These tools are based on ranking functional data by means of notions of depth/outlyingness and make use of methods for functional outlier detections. For univariate functional data, the functional boxplot and surface boxplot are emphasized. For multivariate functional data, the magnitude–shape plot, the two-stage functional boxplot, and the trajectory functional boxplot are described. A bivariate functional dataset of the angles formed by the hip and knee of 39 children over their gait cycles is used throughout for illustration of the various visualization tools.Citation
Genton, M. G., & Sun, Y. (2020). Functional Data Visualization. Wiley StatsRef: Statistics Reference Online, 1–11. doi:10.1002/9781118445112.stat08290Sponsors
This research was supported by the King Abdullah University of Science and Technology (KAUST).Publisher
WileyISBN
9781118445112Additional Links
https://onlinelibrary.wiley.com/doi/10.1002/9781118445112.stat08290ae974a485f413a2113503eed53cd6c53
10.1002/9781118445112.stat08290