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dc.contributor.authorMiettinen, Jari
dc.contributor.authorNordhausen, Klaus
dc.contributor.authorTaskinen, Sara
dc.date.accessioned2019-03-27T08:18:21Z
dc.date.available2019-03-27T08:18:21Z
dc.date.issued2018
dc.identifier.citationMiettinen, J., Nordhausen, K., & Taskinen, S. (2018). fICA : FastICA Algorithms and Their Improved Variants. <i>The R Journal</i>, <i>10</i>(2), 148-158. <a href="https://doi.org/10.32614/rj-2018-046" target="_blank">https://doi.org/10.32614/rj-2018-046</a>
dc.identifier.otherCONVID_28869373
dc.identifier.otherTUTKAID_80368
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/63297
dc.description.abstractAbstract In independent component analysis (ICA) one searches for mutually independent non gaussian latent variables when the components of the multivariate data are assumed to be linear combinations of them. Arguably, the most popular method to perform ICA is FastICA. There are two classical versions, the deflation-based FastICA where the components are found one by one, and the symmetric FastICA where the components are found simultaneously. These methods have been implemented previously in two R packages, fastICA and ica. We present the R package fICA and compare it to the other packages. Additional features in fICA include optimization of the extraction order in the deflation-based version, possibility to use any nonlinearity function, and improvement to convergence of the deflation-based algorithm. The usage of the package is demonstrated by applying it to the real ECG data of a pregnant woman.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherR Foundation for Statistical Computing
dc.relation.ispartofseriesThe R Journal
dc.relation.urihttps://journal.r-project.org/archive/2018/RJ-2018-046/RJ-2018-046.pdf
dc.rightsCC BY 4.0
dc.subject.otheralgorimit
dc.titlefICA : FastICA Algorithms and Their Improved Variants
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201903261978
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.oppiaineTilastotiedefi
dc.contributor.oppiaineStatisticsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2019-03-26T13:15:14Z
dc.description.reviewstatuspeerReviewed
dc.format.pagerange148-158
dc.relation.issn2073-4859
dc.relation.numberinseries2
dc.relation.volume10
dc.type.versionpublishedVersion
dc.rights.copyright© 2019 The Authors
dc.rights.accesslevelopenAccessfi
dc.subject.ysosignaalianalyysi
dc.subject.ysoR-kieli
dc.subject.ysoalgoritmit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p26805
jyx.subject.urihttp://www.yso.fi/onto/yso/p24355
jyx.subject.urihttp://www.yso.fi/onto/yso/p14524
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.32614/rj-2018-046


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