<img src=https://github.com/Mamba413/git_picture/blob/master/scrcss.jpg width=135/> CDC Statistics

Introdution

The fundamental problems for data mining and statistical/machine learning are:

• how to select the important features for ultra high dimensional dataset?
• whether a statistical/machine learning model is sufficient (i.e. does not need to include additional variables)?

CDC Statistics based statistical method provides solutions for these issues.

License

GPL (>= 2)

Reference

• Xueqin Wang, Wenliang Pan, Wenhao Hu, Yuan Tian & Heping Zhang (2015) Conditional Distance Correlation, Journal of the American Statistical Association, 110:512, 1726-1734, DOI: 10.1080/01621459.2014.993081
• Canhong Wen, Wenliang Pan, Mian Huang and Xueqin Wang (2018) Sure independence screening adjusted for confounding covariates with ultrahigh dimensional data, Statistica Sinica, 28 (2018), no. 1, 293--318, DOI:10.5705/ss.202014.0117