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dc.contributor.authorTaskinen, Sara
dc.contributor.authorFrahm, Gabriel
dc.contributor.authorNordhausen, Klaus
dc.contributor.authorOja, Hannu
dc.contributor.editorYi, Mengxi
dc.contributor.editorNordhausen, Klaus
dc.date.accessioned2024-10-25T09:37:17Z
dc.date.available2024-10-25T09:37:17Z
dc.date.issued2023
dc.identifier.citationTaskinen, S., Frahm, G., Nordhausen, K., & Oja, H. (2023). A Review of Tyler’s Shape Matrix and Its Extensions. In M. Yi, & K. Nordhausen (Eds.), <i>Robust and Multivariate Statistical Methods : Festschrift in Honor of David E. Tyler</i> (pp. 23-41). Springer. <a href="https://doi.org/10.1007/978-3-031-22687-8_2" target="_blank">https://doi.org/10.1007/978-3-031-22687-8_2</a>
dc.identifier.otherCONVID_182971282
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/97705
dc.description.abstractIn a seminal paper, Tyler (1987a) suggests an M-estimator for shape, which is now known as Tyler’s shape matrix. Tyler’s shape matrix is increasingly popular due to its nice statistical properties. It is distribution free within the class of generalized elliptical distributions. Further, under very mild regularity conditions, it is consistent and asymptotically normally distributed after the usual standardization. Tyler’s shape matrix is still the subject of active research, e.g., in the signal processing literature, which discusses structured and regularized shape matrices. In this article, we review Tyler’s original shape matrix and some recent developments.en
dc.format.extent495
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofRobust and Multivariate Statistical Methods : Festschrift in Honor of David E. Tyler
dc.rightsIn Copyright
dc.subject.otherM-estimator
dc.subject.othergeneralized elliptical distribution
dc.subject.otherhigh dimension
dc.subject.otherrobust estimator
dc.subject.otherregularization
dc.titleA Review of Tyler’s Shape Matrix and Its Extensions
dc.typebookPart
dc.identifier.urnURN:NBN:fi:jyu-202410256560
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.type.urihttp://purl.org/eprint/type/BookItem
dc.relation.isbn978-3-031-22686-1
dc.type.coarhttp://purl.org/coar/resource_type/c_3248
dc.description.reviewstatuspeerReviewed
dc.format.pagerange23-41
dc.type.versionacceptedVersion
dc.rights.copyright© 2023 the Authors
dc.rights.accesslevelopenAccessfi
dc.subject.ysojakaumat
dc.subject.ysomatriisit
dc.subject.ysoestimointi
dc.subject.ysotilastomenetelmät
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p7185
jyx.subject.urihttp://www.yso.fi/onto/yso/p18099
jyx.subject.urihttp://www.yso.fi/onto/yso/p11349
jyx.subject.urihttp://www.yso.fi/onto/yso/p3127
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-031-22687-8_2
dc.type.okmA3


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