Multivariate Distributions

  • Wolfgang Härdle
  • Léopold Simar


The preceeding chapter showed that by using the two first moments of a multivariate distribution (the mean and the covariance matrix), a lot of information on the relationship between the variables can be made available. Only basic statistical theory was used to derive tests of independence or of linear relationships. In this chapter we give an introduction to the basic probability tools useful in statistical multivariate analysis.


Bootstrap Sample Multivariate Distribution Gaussian Copula Joint Distribution Function Conditional Covariance Matrix 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Wolfgang Härdle
    • 1
  • Léopold Simar
    • 2
  1. 1.CASE — Center for Applied Statistics and Economics, Institut für Statistik und ÖkonometrieHumboldt-Universität zu BerlinBerlinGermany
  2. 2.Inst. StatistiqueUniversité Catholique LouvainLouvain-la-NeuveBelgium

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