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Computationally Intensive Techniques

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Applied Multivariate Statistical Analysis

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Abstract

It is generally accepted that training in statistics must include some exposure to the mechanics of computational statistics. This exposure to computational methods is of an essential nature when we consider extremely high dimensional data. Computer aided techniques can help us to discover dependencies in high dimensions without complicated mathematical tools. A draftman’s plot (i.e. a matrix of pairwise scatterplots like in Figure 1.14) may lead us immediately to a theoretical hypothesis (on a lower dimensional space) on the relationship of the variables. Computer aided techniques are therefore at the heart of multivariate statistical 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). Computationally Intensive Techniques. In: Applied Multivariate Statistical Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17229-8_19

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