On the Conditional Distribution of the Multivariate t Distribution.
As alternatives to the normal distributions, t distributions are widely applied in robust analysis for data with outliers or heavy tails. The properties of the multivariate t distribution are well documented in Kotz and Nadarajah's book, which, however, states a wrong conclusion about the conditiona...
| Publicado en: | American Statistician Vol. 70; no. 3; pp. 293 - 296 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=117908804&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 117908804 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: 2016 vid: 70 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 117908804 10.1080/00031305.2016.1164756 ppf: 293 ppct: 3 formats: tig: atl: On the Conditional Distribution of the Multivariate t Distribution. aug: au: Ding, Peng su: Distribution (Probability theory) Robust statistics Multivariate analysis Statistics Density functional theory sug: subj: Distribution (Probability theory) Robust statistics Multivariate analysis Statistics Density functional theory keyword: Bayes' theorem Data augmentation Mahalanobis distance Normal mixture Representation Bayes' theorem Data augmentation Mahalanobis distance Normal mixture Representation ab: As alternatives to the normal distributions, t distributions are widely applied in robust analysis for data with outliers or heavy tails. The properties of the multivariate t distribution are well documented in Kotz and Nadarajah's book, which, however, states a wrong conclusion about the conditional distribution of the multivariate t distribution. Previous literature has recognized that the conditional distribution of the multivariate t distribution also follows the multivariate t distribution. We provide an intuitive proof without directly manipulating the complicated density function of the multivariate t distribution. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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