Sparse Functional Boxplots for Multivariate Curves

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


This paper introduces the sparse functional boxplot and the intensity sparse functional boxplot as practical exploratory tools. Besides being available for complete functional data, they can be used in sparse univariate and multivariate functional data. The sparse functional boxplot, based on the functional boxplot, displays sparseness proportions within the 50% central region. The intensity sparse functional boxplot indicates the relative intensity of fitted sparse point patterns in the central region. The two-stage functional boxplot, which derives from the functional boxplot to detect outliers, is furthermore extended to its sparse form. We also contribute to sparse data fitting improvement and sparse multivariate functional data depth. In a simulation study, we evaluate the goodness of data fitting, several depth proposals for sparse multivariate functional data, and compare the results of outlier detection between the sparse functional boxplot and its two-stage version. The practical applications of the sparse functional boxplot and intensity sparse functional boxplot are illustrated with two public health datasets. Supplementary materials and codes are available for readers to apply our visualization tools and replicate the analysis
Original languageEnglish (US)
Pages (from-to)1-30
Number of pages30
JournalJournal of Computational and Graphical Statistics
StatePublished - Apr 19 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-26
Acknowledgements: This research was supported by the King Abdullah University of Science and Technology (KAUST)

ASJC Scopus subject areas

  • Discrete Mathematics and Combinatorics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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