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Multivariate Distributions

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Applied Multivariate Statistical Analysis

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Abstract

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.

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Authors and Affiliations

  1. L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ., School of Business and Economics, Humboldt-Universität zu Berlin, Berlin, Germany

    Wolfgang Karl Härdle

  2. Inst. Statistics, Center of Operations Research & Econometrics (CORE), Katholieke Universiteit Leuven, Leuven, Belgium

    Léopold Simar

Authors
  1. Wolfgang Karl Härdle
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  2. Léopold Simar
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© 2012 Springer-Verlag Berlin Heidelberg

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Härdle, W.K., Simar, L. (2012). Multivariate Distributions. In: Applied Multivariate Statistical Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17229-8_4

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