Curve boxplot: Generalization of boxplot for ensembles of curves

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Publication Type pre-print
School or College College of Engineering
Department Computing, School of
Creator Whitaker, Ross T.
Other Author Mirzargar, Mahsa; Kirby, Robert M.
Title Curve boxplot: Generalization of boxplot for ensembles of curves
Date 2014-01-01
Description In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Volume 20
Issue 12
First Page 2654
Last Page 2663
Language eng
Bibliographic Citation Mirzargar, M., Whitaker, R. T., & Kirby, R. M. (2014). Curve boxplot: Generalization of boxplot for ensembles of curves. IEEE Transactions on Visualization and Computer Graphics, 20(12), 2654-63.
Rights Management (c) 2014 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 2,243,592 bytes
Identifier uspace,19074
ARK ark:/87278/s6dg019h
Setname ir_uspace
Date Created 2014-12-08
Date Modified 2021-05-06
ID 712739
Reference URL https://collections.lib.utah.edu/ark:/87278/s6dg019h
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