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Permutation-based multivariate regression analysis: The case for least sum of absolute deviations regression

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Abstract

Linear and nonlinear multivariate least sum of absolute deviations regression models are profiled and evaluated. A chance-corrected measure of agreement between observed and predicted values is presented, a technique for establishing empirically-derived quantile limits for predicted values is introduced, and a permutation-based inference procedure for the measure of agreement is described.

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Authors
  1. Paul W. Mielke Jr.
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  2. Kenneth J. Berry
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Mielke, P.W., Berry, K.J. Permutation-based multivariate regression analysis: The case for least sum of absolute deviations regression. Annals of Operations Research 74, 259–268 (1997). https://doi.org/10.1023/A:1018926522359

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