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dc.contributor.authorTempl, Matthias-
dc.contributor.authorHron, Karel-
dc.contributor.authorFilzmoser, Peter-
dc.date.accessioned2018-05-24T06:40:45Z-
dc.date.available2018-05-24T06:40:45Z-
dc.date.issued2017-
dc.identifier.urihttp://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdfde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/6034-
dc.description.abstractThe analysis of compositional data using the log-ratio approach is based on ratios between compositional parts. Zeros in the parts thus cause serious difficulties for the analysis. This is a particular problem in presence of structural zeros, resulting from a structural process rather than from imprecision of a measurement device. Examples of structural zeros in compositional data are, e.g. expenditures in tobacco for non-smokers, tax payments on shares for non-share holders, time budget on sports for people who do not do any sports at all, etc. Therefore, structural zeros cannot be simply replaced by a non-zero value as it is done, e.g. for values below detection limit or missing values. Instead, zeros have to be incorporated into further statistical processing. We lay the focus on exploratory tools for identifying outliers in compositional data sets with structural zeros. For this purpose, robust Mahalanobis distances are estimated; they are computed either directly for subcompositions determined by their zero patterns or by using imputation as an auxiliary step to improve the efficiency of the estimates. Consequently, we proceed to the subcompositional and subgroup level. For this approach, new theory is formulated that allows to estimate covariances for imputed compositional data and to apply estimations on subgroups using blocks of this covariance matrix (Templ, Hron and Filzmoser, 2016). Moreover, the zero pattern structure is analyzed using PCA for binary data (de Leeuw, 2016) to achieve a comprehensive view of the overall multivariate structure of zeros. The proposed tools are applied to large-scale data from official statistics, where the need for an appropriate treatment of zeros is obvious.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectCompositional data analysisde_CH
dc.subject.ddc510: Mathematikde_CH
dc.titleExploring outliers in compositional data with structural zerosde_CH
dc.typeKonferenz: Sonstigesde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.conference.detailsCoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
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Templ, M., Hron, K., & Filzmoser, P. (2017). Exploring outliers in compositional data with structural zeros. CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017. http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf
Templ, M., Hron, K. and Filzmoser, P. (2017) ‘Exploring outliers in compositional data with structural zeros’, in CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017. Available at: http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf.
M. Templ, K. Hron, and P. Filzmoser, “Exploring outliers in compositional data with structural zeros,” in CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017, 2017. [Online]. Available: http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf
TEMPL, Matthias, Karel HRON und Peter FILZMOSER, 2017. Exploring outliers in compositional data with structural zeros. In: CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017 [online]. Conference presentation. 2017. Verfügbar unter: http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf
Templ, Matthias, Karel Hron, and Peter Filzmoser. 2017. “Exploring Outliers in Compositional Data with Structural Zeros.” Conference presentation. In CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017. http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf.
Templ, Matthias, et al. “Exploring Outliers in Compositional Data with Structural Zeros.” CoDaWork 2017: 7th International Workshop on Compositional Data Analysis, Siena, Italy, 5-9 June 2017, 2017, http://www.compositionaldata.com/codawork2017/abstracts/8thThursday/Oral/ZER-2.pdf.


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