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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.

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Author information

Authors and Affiliations

  1. Ladislaus von Bortkiewicz Chair of Statistics, Humboldt-Universität zu Berlin, Berlin, Germany

    Wolfgang Karl Härdle

  2. Institute of Statistics, Biostatistics and Actuarial Sciences, Université Catholique de Louvain, Louvain-la-Neuve, Belgium

    Léopold Simar

Authors
  1. Wolfgang Karl Härdle
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  2. Léopold Simar
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Correspondence to Wolfgang Karl Härdle .

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Härdle, W.K., Simar, L. (2019). Computationally Intensive Techniques. In: Applied Multivariate Statistical Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-26006-4_20

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