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dc.contributor.authorSun, Ying
dc.contributor.authorHart, Jeffrey D.
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2016-01-19T13:20:31Z
dc.date.available2016-01-19T13:20:31Z
dc.date.issued2013-08-26
dc.identifier.citationSun Y, Hart JD, Genton MG (2013) Improved nonparametric inference for multiple correlated periodic sequences. Stat 2: 197–210. Available: http://dx.doi.org/10.1002/sta4.28.
dc.identifier.issn2049-1573
dc.identifier.doi10.1002/sta4.28
dc.identifier.urihttp://hdl.handle.net/10754/594060
dc.description.abstractThis paper proposes a cross-validation method for estimating the period as well as the values of multiple correlated periodic sequences when data are observed at evenly spaced time points. The period of interest is estimated conditional on the other correlated sequences. An alternative method for period estimation based on Akaike's information criterion is also discussed. The improvement of the period estimation performance is investigated both theoretically and by simulation. We apply the multivariate cross-validation method to the temperature data obtained from multiple ice cores, investigating the periodicity of the El Niño effect. Our methodology is also illustrated by estimating patients' cardiac cycle from different physiological signals, including arterial blood pressure, electrocardiography, and fingertip plethysmograph.
dc.publisherWiley
dc.subjectCross-validation
dc.subjectModel selection
dc.subjectMultiple sequences
dc.subjectNonparametric estimation
dc.subjectPeriod
dc.titleImproved nonparametric inference for multiple correlated periodic sequences
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalStat
dc.contributor.institutionDepartment of Statistics; University of Chicago; Chicago IL 60637 USA
dc.contributor.institutionDepartment of Statistics; Texas A&M University; College Station TX 77843 USA
kaust.personGenton, Marc G.
dc.date.published-online2013-08-26
dc.date.published-print2013-12


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