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An empirical study of PLAD regression using the bootstrap

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Abstract

Partial LAD regression uses the L 1 norm associated with least absolute deviations (LAD) regression while retaining the same algorithmic structure of univariate partial least squares (PLS) regression. We use the bootstrap in order to assess the partial LAD regression model performance and to make comparisons to PLS regression. We use a variety of examples coming from NIR experiments as well as two sets of experimental data.

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Authors and Affiliations

  1. Statistical Institute, University of Neuchâtel, Neuchâtel, Switzerland

    Athanassios Kondylis

  2. Department of Mathematics and Statistics, Lancaster University, Lancaster, England

    Joe Whittaker

Authors
  1. Athanassios Kondylis
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  2. Joe Whittaker
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Correspondence to Athanassios Kondylis.

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Kondylis, A., Whittaker, J. An empirical study of PLAD regression using the bootstrap. Computational Statistics 22, 307–321 (2007). https://doi.org/10.1007/s00180-007-0034-3

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