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Search for relevant sets of variables in a high‐dimensional setup keeping the familywise error rate

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  • Jürgen Läuter
  • Ekkehard Glimm
  • Markus Eszlinger

Abstract

Two multiple procedures for the detection of relevant sets of variables in a high‐dimensional problem are suggested. Multivariate tests for significance are combined with the search for interpretable multivariate structures. Thus, groups of highly correlated variables are investigated. The emphasis lies on managing the huge number of possible subsets, for example, in gene expression analysis. The first procedure is based on parametric spherical tests and an order relation of the subsets. The second procedure is a non‐parametric method utilizing Westfall–Young principles.

Suggested Citation

  • Jürgen Läuter & Ekkehard Glimm & Markus Eszlinger, 2005. "Search for relevant sets of variables in a high‐dimensional setup keeping the familywise error rate," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(3), pages 298-312, August.
    • Handle: RePEc:bla:stanee:v:59:y:2005:i:3:p:298-312
    DOI: 10.1111/j.1467-9574.2005.00290.x
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    Cited by:

    1. Finos, Livio, 2011. "A note on Left-Spherically Distributed test with covariates," Statistics & Probability Letters, Elsevier, vol. 81(6), pages 639-641, June.
    2. Kropf, Siegfried & Läuter, Jürgen & Kose, Daniela & von Rosen, Dietrich, 2009. "Comparison of exact parametric tests for high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 776-787, January.

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