Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/43691

TitleChange-point detection in environmental time series based on the informational approach
Author(s)Costa, Marco
Gonçalves, A. Manuela
Teixeira, Lara
KeywordsChange-point detection
Water quality data
Schwarz information criterion
Mean and variance shift
Simulation study
Issue date2016
PublisherEse - Salento University Publishing
JournalElectronic Journal of Applied Statistical Analysis
CitationCosta, M., Goncalves, A. M., & Teixeira, L. (2016). Change-point detection in environmental time series based on the informational approach. Electronic Journal of Applied Statistical Analysis, 9(2), 267-296. doi: 10.1285/i20705948v9n2p267
Abstract(s)In this study, the Schwarz Information Criterion (SIC) is applied in order to detect change-points in the time series of surface water quality variables. The application of change-point analysis allowed detecting change-points in both the mean and the variance in series under study. Time variations in environmental data are complex and they can hinder the identi cation of the so-called change-points when traditional models are applied to this type of problems. The assumptions of normality and uncorrelation are not present in some time series, and so, a simulation study is carried out in order to evaluate the methodology's performance when applied to non-normal data and/or with time correlation.
TypeArticle
URIhttp://hdl.handle.net/1822/43691
DOI10.1285/i20705948v9n2p267
ISSN2070-5948
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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