Timeline for Estimating direction from a distribution on a circle
Current License: CC BY-SA 2.5
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 20, 2010 at 13:07 | vote | accept | Andrei Kolin | ||
| Oct 16, 2010 at 10:42 | comment | added | Andrei Kolin | Niels, thanks a lot! I didn't know the RMS concept. If i did it might ring a bell. It's indeed THE best answer in the sense i asked for. | |
| Oct 16, 2010 at 10:38 | vote | accept | Andrei Kolin | ||
| Oct 16, 2010 at 10:39 | |||||
| Oct 15, 2010 at 3:24 | comment | added | Robby McKilliam | I think, due to the symmetry, it essential does act in a linear way. I'm pretty sure I can describe very accurately how well your estimator will work. I'll post this as an(other) answer a bit later. | |
| Oct 15, 2010 at 2:31 | comment | added | Niels J. Diepeveen | In principle the stretching of the squaring is undone by the shrinking of the square root. I do see a potential problem with the arithmetic mean getting smaller in absolute value, especially if the distribution is rather flat, but I don't think that's a linear effect, is it? | |
| Oct 15, 2010 at 2:00 | comment | added | Robby McKilliam | Actually, I lie. In this case, I think this is exactly what you want to do! I recommend this answer be marked as correct. My answers can just be considered as advertising for the important and interesting the field of circular statistics. | |
| Oct 15, 2010 at 1:13 | comment | added | Robby McKilliam | That's a good answer Niels, and I believe it will work quite well in this case. One trouble I see is that by squaring you have multiplied the 'noise' (if you like) by 2. So, I think that this estimator will be consistent, but not efficient. | |
| Oct 15, 2010 at 0:39 | history | answered | Niels J. Diepeveen | CC BY-SA 2.5 |