Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Filzmoser, Peter | - |
dc.contributor.author | Lubbe, Sugnet | - |
dc.contributor.author | Templ, Matthias | - |
dc.date.accessioned | 2021-03-14T11:22:18Z | - |
dc.date.available | 2021-03-14T11:22:18Z | - |
dc.date.issued | 2020-11-07 | - |
dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/21997 | - |
dc.description.abstract | Modern applications in chemometrics and bioinformatics result in compositional data sets with a high proportion of zeros. An example are microbiome data, where zeros refer to measurements below the detection limit of one count. When building statistical models, it is important that zeros are replaced by sensible values. Different replacement techniques from compositional data analysis are considered and compared by a simulation study and examples. The comparison also includes a recently proposed method [1] based on deep learning. Detailed insights into the appropriateness of the methods for a problem at hand are provided, and differences in the outcomes of statistical results are discussed. | de_CH |
dc.language.iso | en | de_CH |
dc.rights | Licence according to publishing contract | de_CH |
dc.subject | Compositional data | de_CH |
dc.subject | Biomic data | de_CH |
dc.subject | High-dimensional data | de_CH |
dc.subject | Rounded zeros | de_CH |
dc.subject | Imputation | de_CH |
dc.subject | Replacement | de_CH |
dc.subject.ddc | 005: Computerprogrammierung, Programme und Daten | de_CH |
dc.title | Strategies to replace high proportions of zeros in compositional data | de_CH |
dc.type | Konferenz: Sonstiges | de_CH |
dcterms.type | Text | de_CH |
zhaw.departement | School of Engineering | de_CH |
zhaw.organisationalunit | Institut für Datenanalyse und Prozessdesign (IDP) | de_CH |
zhaw.conference.details | 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020 | de_CH |
zhaw.funding.eu | No | de_CH |
zhaw.originated.zhaw | Yes | de_CH |
zhaw.publication.status | publishedVersion | de_CH |
zhaw.publication.review | Peer review (Abstract) | de_CH |
zhaw.webfeed | Statistik und Quantitative Finance | de_CH |
zhaw.author.additional | No | de_CH |
zhaw.display.portrait | Yes | de_CH |
Appears in collections: | Publikationen School of Engineering |
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Filzmoser, P., Lubbe, S., & Templ, M. (2020, November 7). Strategies to replace high proportions of zeros in compositional data. 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020.
Filzmoser, P., Lubbe, S. and Templ, M. (2020) ‘Strategies to replace high proportions of zeros in compositional data’, in 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020.
P. Filzmoser, S. Lubbe, and M. Templ, “Strategies to replace high proportions of zeros in compositional data,” in 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020, Nov. 2020.
FILZMOSER, Peter, Sugnet LUBBE und Matthias TEMPL, 2020. Strategies to replace high proportions of zeros in compositional data. In: 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020. Conference presentation. 7 November 2020
Filzmoser, Peter, Sugnet Lubbe, and Matthias Templ. 2020. “Strategies to Replace High Proportions of Zeros in Compositional Data.” Conference presentation. In 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020.
Filzmoser, Peter, et al. “Strategies to Replace High Proportions of Zeros in Compositional Data.” 1st Conference on Information Technology and Data Science, CITDS, Debrecen, Hungary / Online, 6-8 November 2020, 2020.
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