A folded model for compositional data analysis

dc.contributor.authorTsagris, Michail
dc.contributor.authorStewart, Connie
dc.date.accessioned2023-06-06T14:26:45Z
dc.date.available2023-06-06T14:26:45Z
dc.date.issued2020
dc.description.abstractA folded type model is developed for analysing compositional data. The proposed model involves an extension of the α-transformation for compositional data and provides a new and flexible class of distributions for modelling data defined on the simplex sample space. Despite its rather seemingly complex structure, employment of the EM algorithm guarantees efficient parameter estimation. The model is validated through simulation studies and examples which illustrate that the proposed model performs better in terms of capturing the data structure, when compared to the popular logistic normal distribution, and can be advantageous over a similar model without folding.
dc.description.copyrightThis is the peer reviewed version of the following article: [A folded model for compositional data analysis. Australian & New Zealand Journal of Statistics 62, 2 p249-277 (2020)], which has been published in final form at https://doi.org/10.1111/anzs.12289
dc.identifier.doi10.1111/anzs.12289
dc.identifier.issn1369-1473
dc.identifier.issn1467-842X
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/26269
dc.language.isoen
dc.publisherWiley
dc.relation.hasversionhttps://doi.org/10.1111/anzs.12289
dc.relation.ispartofAustralian & New Zealand Journal of Statistics
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.titleA folded model for compositional data analysis
dc.typejournal-article
oaire.citation.endPage277
oaire.citation.issue2
oaire.citation.startPage249
oaire.citation.titleAustralian & New Zealand Journal of Statistics
oaire.citation.volume62
oaire.license.conditionother
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa

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