TY - CHAP
T1 - Functional Data Visualization
AU - Genton, Marc G.
AU - Sun, Ying
N1 - KAUST Repository Item: Exported on 2021-03-02
Acknowledgements: This research was supported by the King Abdullah University of Science and Technology (KAUST).
PY - 2020/11/4
Y1 - 2020/11/4
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/667759
UR - https://onlinelibrary.wiley.com/doi/10.1002/9781118445112.stat08290
U2 - 10.1002/9781118445112.stat08290
DO - 10.1002/9781118445112.stat08290
M3 - Chapter
SN - 9781118445112
SP - 1
EP - 11
BT - Wiley StatsRef: Statistics Reference Online
PB - Wiley
ER -