Timeline for Distance of distributions of random variables, without PDF
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| S Mar 1, 2017 at 21:00 | history | suggested | Henry.L |
correct tags, it is not an ode-analysis problem.
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| Mar 1, 2017 at 20:13 | answer | added | Henry.L | timeline score: 2 | |
| Mar 1, 2017 at 20:10 | review | Suggested edits | |||
| S Mar 1, 2017 at 21:00 | |||||
| Feb 27, 2017 at 23:22 | comment | added | Anthony Quas | In the case where $\mu$ is Lebesgue, you just take the (compositional) inverse of the cdf. | |
| Feb 27, 2017 at 21:26 | comment | added | Amir Sagiv | @AnthonyQuas Even if they're not smooth? How? | |
| Feb 27, 2017 at 18:30 | comment | added | Anthony Quas | There is always an increasing rearrangement. | |
| Feb 27, 2017 at 17:44 | comment | added | Amir Sagiv | Thanks! Unfortunately no, they're not monotone. @AnthonyQuas | |
| Feb 27, 2017 at 4:19 | comment | added | Anthony Quas | Are you willing to add the assumption that the two functions are increasing? In that case, the integral of the difference is a measure of the distance between the distributions. It's also reasonably robust. | |
| Feb 26, 2017 at 21:25 | history | edited | Amir Sagiv | CC BY-SA 3.0 |
corrected details of distribution
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| Feb 26, 2017 at 21:14 | history | asked | Amir Sagiv | CC BY-SA 3.0 |