Timeline for Distance between random variables?
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 7, 2016 at 10:25 | vote | accept | mic | ||
| Sep 14, 2015 at 7:18 | comment | added | mic | Mutual information could help indeed. But then, one does not measure similarity in distribution, cf. Bey answer for a baseline motivation. | |
| Sep 13, 2015 at 23:27 | comment | added | seanv507 | I don't understand your criticism of divergence measures... Why doesn't mutual information provide you 'non linear' correlation | |
| Sep 13, 2015 at 23:18 | answer | added | user75138 | timeline score: 1 | |
| Sep 13, 2015 at 22:20 | comment | added | mic | Not necessarily linearly correlated, it could be "linearly" correlated up to some monotonous transforms or even a broader notion of "correlation". | |
| Sep 13, 2015 at 20:01 | comment | added | user75138 | So if we have such a distance $d(\mathbf{X,Y})$ then $d=0$ iff $X,Y$ come from the same distribution and are perfectly (linearly?) correlated? | |
| Sep 13, 2015 at 19:22 | comment | added | mic | A perfect dependence between the two random variables AND the same distribution would result in zero distance. Would you suggest any other property? I think that a reasonable distance should take into account dependence and distribution since it amounts for the whole distribution according to Sklar's theorem in copula theory. | |
| Sep 13, 2015 at 2:18 | comment | added | user75138 | This needs to be tightened up a bit. What property of two random variables would result in zero distance? | |
| Sep 12, 2015 at 10:51 | history | asked | mic | CC BY-SA 3.0 |