Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

Handle URI:
http://hdl.handle.net/10754/597468
Title:
Adjusted functional boxplots for spatio-temporal data visualization and outlier detection
Authors:
Sun, Ying; Genton, Marc G.
Abstract:
This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.
Citation:
Sun Y, Genton MG (2011) Adjusted functional boxplots for spatio-temporal data visualization and outlier detection. Environmetrics 23: 54–64. Available: http://dx.doi.org/10.1002/env.1136.
Publisher:
Wiley-Blackwell
Journal:
Environmetrics
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
24-Oct-2011
DOI:
10.1002/env.1136
Type:
Article
ISSN:
1180-4009
Sponsors:
This research was partially supported by NSF grants DMS-1007504, DMS-1100492, and Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). The authors thank the Guest Editor, two referees and Noel Cressie for helpful comments, as well as Caspar M. Ammann for providing the GCM data.
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Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorSun, Yingen
dc.contributor.authorGenton, Marc G.en
dc.date.accessioned2016-02-25T12:40:19Zen
dc.date.available2016-02-25T12:40:19Zen
dc.date.issued2011-10-24en
dc.identifier.citationSun Y, Genton MG (2011) Adjusted functional boxplots for spatio-temporal data visualization and outlier detection. Environmetrics 23: 54–64. Available: http://dx.doi.org/10.1002/env.1136.en
dc.identifier.issn1180-4009en
dc.identifier.doi10.1002/env.1136en
dc.identifier.urihttp://hdl.handle.net/10754/597468en
dc.description.abstractThis article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.en
dc.description.sponsorshipThis research was partially supported by NSF grants DMS-1007504, DMS-1100492, and Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). The authors thank the Guest Editor, two referees and Noel Cressie for helpful comments, as well as Caspar M. Ammann for providing the GCM data.en
dc.publisherWiley-Blackwellen
dc.subjectFunctional dataen
dc.subjectGCM dataen
dc.subjectOutlier detectionen
dc.subjectPrecipitation dataen
dc.subjectRobust covarianceen
dc.subjectSpatio-temporal dataen
dc.titleAdjusted functional boxplots for spatio-temporal data visualization and outlier detectionen
dc.typeArticleen
dc.identifier.journalEnvironmetricsen
dc.contributor.institutionStatistical and Applied Mathematical Sciences Institute; 19 T.W. Alexander Drive, Research Triangle Park; NC 27709-4006; USAen
dc.contributor.institutionDepartment of Statistics; Texas A&M University, College Station; TX 77843-3143; USAen
kaust.grant.numberKUS-C1-016-04en
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