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Theory of the Multinormal

  • Wolfgang Karl HärdleEmail author
  • Léopold Simar
Chapter

Abstract

In the preceding 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.

References

  1. K.T. Fang, S. Kotz, K.W. Ng, Symmetric Multivariate and Related Distributions (Chapman and Hall, London, 1990)CrossRefGoogle Scholar
  2. K.V. Mardia, J.T. Kent, J.M. Bibby, Multivariate Analysis (Academic Press, Duluth, London, 1979)zbMATHGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Ladislaus von Bortkiewicz Chair of StatisticsHumboldt-Universität zu BerlinBerlinGermany
  2. 2.Institute of Statistics, Biostatistics and Actuarial SciencesUniversité Catholique de LouvainLouvain-la-NeuveBelgium

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