- 著者
-
Masashi SUGIYAMA
Taiji SUZUKI
- 出版者
- The Institute of Electronics, Information and Communication Engineers
- 雑誌
- IEICE Transactions on Information and Systems (ISSN:09168532)
- 巻号頁・発行日
- vol.E94.D, no.6, pp.1333-1336, 2011-06-01 (Released:2011-06-01)
- 参考文献数
- 10
- 被引用文献数
-
6
10
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.