Theory of the Multinormal

Wolfgang Härdle () and Léopold Simar ()
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Wolfgang Härdle: Humboldt-Universität zu Berlin, CASE — Center for Applied Statistics and Economics, Institut für Statistik und Ökonometrie
Léopold Simar: Université Catholique Louvain, Inst. Statistique

Chapter 5 in Applied Multivariate Statistical Analysis, 2003, pp 155-171 from Springer

Abstract: Abstract In the preceeding chapter we saw how the multivariate normal distribution comes into play in many applications. It is useful to know more about this distribution, since it is often a good approximate distribution in many situations. Another reason for considering the multinormal distribution relies on the fact that it has many appealing properties: it is stable under linear transforms, zero correlation corresponds to independence, the marginals and all the conditionals are also multivariate normal variates, etc. The mathematical properties of the multinormal make analyses much simpler.

Keywords: Random Vector; Multivariate Normal Distribution; Sample Covariance Matrix; Wishart Distribution; Elliptical Distribution (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1007/978-3-662-05802-2_5

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