Least-Squares Independence Test

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概要

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• Identifying the statistical independence of random variables is one of the important tasks in statistical data analysis. In this paper, we propose a novel non-parametric independence test based on a least-squares density ratio estimator. Our method, called least-squares independence test (LSIT), is distribution-free, and thus it is more flexible than parametric approaches. Furthermore, it is equipped with a model selection procedure based on cross-validation. This is a significant advantage over existing non-parametric approaches which often require manual parameter tuning. The usefulness of the proposed method is shown through numerical experiments.

• 2011-06-01

著者

• Sugiyama Masashi

  Tokyo Inst. Of Technol.

• SUZUKI Taiji

  The University of Tokyo

• Suzuki Taiji

  The Univ. Of Tokyo

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