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dc.contributor.authorSun, Ying
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2016-02-25T12:40:19Z
dc.date.available2016-02-25T12:40:19Z
dc.date.issued2011-10-24
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.
dc.identifier.issn1180-4009
dc.identifier.doi10.1002/env.1136
dc.identifier.urihttp://hdl.handle.net/10754/597468
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.
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.
dc.publisherWiley-Blackwell
dc.subjectFunctional data
dc.subjectGCM data
dc.subjectOutlier detection
dc.subjectPrecipitation data
dc.subjectRobust covariance
dc.subjectSpatio-temporal data
dc.titleAdjusted functional boxplots for spatio-temporal data visualization and outlier detection
dc.typeArticle
dc.identifier.journalEnvironmetrics
dc.contributor.institutionStatistical and Applied Mathematical Sciences Institute; 19 T.W. Alexander Drive, Research Triangle Park; NC 27709-4006; USA
dc.contributor.institutionDepartment of Statistics; Texas A&M University, College Station; TX 77843-3143; USA
kaust.grant.numberKUS-C1-016-04


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