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Multivariate location and scatter models

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Part of the book series: Lecture Notes in Statistics ((LNS,volume 199))

Abstract

In this chapter we first introduce and describe different symmetrical and asymmetrical parametric and semiparametric (linear) models which are then later used as the model assumptions in the statistical analysis. The models discussed include multivariate normal distribution N p (μ,Σ) and its different extensions including multivariate t distribution t v,p (μ,Σ) distribution, multivariate elliptical distribution (μ,Σ,ρ) as well as still wider semiparametric symmetrical models. Also some models with skew distributions (generalized elliptical model, mixture models, skew-elliptical model, independent component model) are briefly discussed.

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Correspondence to Hannu Oja .

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© 2010 Springer Science+Business Media, LLC

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Oja, H. (2010). Multivariate location and scatter models. In: Multivariate Nonparametric Methods with R. Lecture Notes in Statistics(), vol 199. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0468-3_2

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