Timeline for What is a good method to find random points on the n-sphere when n is large?
Current License: CC BY-SA 3.0
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| May 22, 2015 at 14:45 | history | edited | user9072 |
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| Jul 11, 2013 at 16:43 | answer | added | user1462620 | timeline score: -3 | |
| Jul 11, 2013 at 15:55 | vote | accept | Dick Palais | ||
| Jul 11, 2013 at 5:41 | history | edited | Ori Gurel-Gurevich |
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| Jul 11, 2013 at 1:01 | comment | added | cardinal | Just an aside: This is treated, e.g., on the Wikipedia page for $n$-sphere and (very closely related) versions of it have been asked previously on stats.SE and math.SE. Similar algorithms exist for generating uniform points on the simplex. | |
| Jul 10, 2013 at 21:35 | answer | added | J.J. Green | timeline score: 13 | |
| Jul 10, 2013 at 20:36 | answer | added | Vidit Nanda | timeline score: 9 | |
| Jul 10, 2013 at 19:26 | comment | added | Ian Agol | (I meant the central limit theorem, not the law of large numbers, but it looks like you've received some answers addressing approximating a normal distribution) | |
| Jul 10, 2013 at 19:17 | answer | added | Mark Meckes | timeline score: 33 | |
| Jul 10, 2013 at 19:16 | answer | added | jjcale | timeline score: 14 | |
| Jul 10, 2013 at 19:11 | comment | added | Ian Agol | I don't know how to do this, but one abstract way to choose a random point on the sphere is to choose the coordinates according to a Gaussian distribution. The resulting random point will be chosen rotationally-symmetrically, so one can then divide by the length to get a point on the sphere chosen randomly and rotationally symmetrically. So if one had a way to approximate a Gaussian distribution, then this should be possible (and I suppose the law of large numbers says that one should be able to do this starting with any probability distribution...). | |
| Jul 10, 2013 at 19:05 | history | asked | Dick Palais | CC BY-SA 3.0 |