Dependence Measure for non-additive model
Abstract
We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two sets of variables based on copula. It is robust to outliers, easy to implement, powerful and appropriate to high-dimensional variables. These properties are important in many applications. Experimental results show that CDC can detect the dependence between variables in both additive and non-additive models.
- Publication:
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arXiv e-prints
- Pub Date:
- October 2013
- DOI:
- 10.48550/arXiv.1310.1562
- arXiv:
- arXiv:1310.1562
- Bibcode:
- 2013arXiv1310.1562J
- Keywords:
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- Statistics - Machine Learning
- E-Print:
- This paper has been withdrawn by the author due to change of the main content