Näytä suppeat kuvailutiedot

dc.contributor.authorKankainen, Annaliisa
dc.contributor.authorTaskinen, Sara
dc.contributor.authorOja, Hannu
dc.date.accessioned2012-11-30T12:01:13Z
dc.date.available2012-11-30T12:01:13Z
dc.date.issued2007fi
dc.identifier.citationKankainen, A., Taskinen, S., & Oja, H. (2007). Tests of multinormality based on location vectors and scatter matrices. <em>Stat. Methods Appl.</em>, 16 (3), 357-379. <a href="http://dx.doi.org/10.1007/s10260-007-0045-9">doi:10.1007/s10260-007-0045-9</a>fi
dc.identifier.otherTUTKAID_28711
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/40494
dc.description.abstractClassical univariate measures of asymmetry such as Pearson’s (mean-median)/σ or (mean-mode)/σ often measure the standardized distance between two separate location parameters and have been widely used in assessing univariate normality. Similarly, measures of univariate kurtosis are often just ratios of two scale measures. The classical standardized fourth moment and the ratio of the mean deviation to the standard deviation serve as examples. In this paper we consider tests of multinormality which are based on the Mahalanobis distance between two multivariate location vector estimates or on the (matrix) distance between two scatter matrix estimates, respectively. Asymptotic theory is developed to provide approximate null distributions as well as to consider asymptotic efficiencies. Limiting Pitman efficiencies for contiguous sequences of contaminated normal distributions are calculated and the efficiencies are compared to those of the classical tests by Mardia. Simulations are used to compare finite sample efficiencies. The theory is also illustrated by an example.fi
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofseriesStatistical Methods and Applications
dc.subject.otherAffine invariancefi
dc.subject.otherKurtosisfi
dc.subject.otherPitman efficiencyfi
dc.subject.otherSkewnessfi
dc.titleTests of multinormality based on location vectors and scatter matricesfi
dc.typeArticle
dc.identifier.urnURN:NBN:fi:jyu-201211293125
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.oppiaineTilastotiedefi
dc.type.urihttp://purl.org/eprint/type/SubmittedJournalArticle
dc.identifier.doi10.1007/s10260-007-0045-9
dc.date.updated2012-11-29T10:40:04Z
dc.type.coarjournal article
dc.description.reviewstatuspeerReviewed
dc.format.pagerange357-379
dc.relation.issn1618-2510
dc.relation.numberinseries3
dc.relation.volume16
dc.type.versionsubmittedVersion
dc.rights.copyright© Springer. This is a manuscript of an article whose final and definitive form has been published by Springer.
dc.rights.accesslevelopenAccessfi


Aineistoon kuuluvat tiedostot

Thumbnail

Aineisto kuuluu seuraaviin kokoelmiin

Näytä suppeat kuvailutiedot