Timeline for Generate data with a given covariance matrix and given non-normal distribution
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Sep 30, 2019 at 12:44 | answer | added | kjetil b halvorsen♦ | timeline score: 1 | |
| Sep 30, 2019 at 11:13 | answer | added | rasmodius | timeline score: 0 | |
| Sep 30, 2019 at 7:37 | history | edited | Wrzlprmft | CC BY-SA 4.0 |
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| Sep 28, 2019 at 3:56 | comment | added | Dave | I think this is along the lines of what I described here: stats.stackexchange.com/a/423189/247274. You specify the correlations in the copula; then you give the marginal distributions parameters to turn those correlations into the covariances you want. | |
| Sep 28, 2019 at 3:17 | history | edited | kjetil b halvorsen♦ |
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| Mar 31, 2019 at 6:35 | comment | added | Wrzlprmft | @user1587692: I am aware of those (or rather, it is not surprising to me that I can generate data from them), but how are they going to help me beyond what I elaborated in the last point? Can you elaborate in an answer? | |
| Mar 30, 2019 at 10:06 | comment | added | user1587692 | Check out elliptical distributions. If you're happy to take one of those the problem is not too bad ( and that you talk about ranks suggests you would like an elliptical distribution...) | |
| Mar 30, 2019 at 7:26 | history | asked | Wrzlprmft | CC BY-SA 4.0 |