Brief
| Seminar Title | Conditional distance correlation |
|---|---|
| Start Date | 2015-04-17 14:00:00 |
| End Date | 2015-04-17 15:30:00 |
| Introduction | Topic: Conditional distance correlation\r\nLocation: 口腔大樓一樓會議室\r\nSpeaker:王學欽教授 (廣州中山大學數學與計算科學學院和中山醫學院雙聘教授)\r\nAbstract: Statistical inference on conditional dependence is essential in many fields including genetic association studies and graphical models. The classic measures focus on linear conditional correlations, and are incapable of characterizing non-linear conditional relationship including non-monotonic relationship. To overcome this limitation, we introduces a nonparametric measure of conditional dependence for multivariate random variables with arbitrary dimensions. Our measure possesses the necessary and intuitive properties as a correlation index. Briefly, it is zero almost surely if and only if two multivariate random variables are conditionally independent given a third random variable. More importantly, the sample version of this measure can be expressed elegantly as the root of a V or U-process with random kernels and has desirable theoretical properties. Based on the sample version, we propose a test for conditional independence, which is proven to be more powerful than some recently developed tests through our numerical simulations. |
| Contact Email | pwu3@tmu.edu.tw |
| Reference link | http://biostat.tmu.edu.tw/ |
| Sign-up Date | 2015-04-07 00:00:00 |
| Sign-up Deadline | 2015-04-17 09:00:00 |
| Seat Limit | 15 |
| Signee Date | 3 |
| Attached file |
