Sorry for the earlier post.
I realized that I was running an older version of MATLAB (7.1). I have now installed the latest release (2009b) and your function appears to work.
Thanks again for these helpful tools!
Thank you for these good demos, Glen! I found you via the NaturalPoint help forum.
I have downloaded both this package and TT_Tools_demo, hoping to get a developmental "leg up".
I encountered a problem right off the bat with this file. I am using V100R2:FLEX cameras. Currently I have only one camera attached (and no hub). When I attempt to run this function, I receive the following output:
Number of cameras = 2
??? Error using ==> registerevent
Input must be a scalar handle.
Error in ==> optitrack_data at 31
The function reports 2 cameras because I have a Hardware Key (for the TT software license) installed; when I remove the key, the camera count drops to 1 but the error is the same. Any thoughts, or is this simply a problem with V100R2:FLEX cameras (as opposed to the TrackIR4 for which you developed this code)?
Marc, thanks, you are right.
I generated a von mises distribution with the mu and kappa estimated from my angles, say x, i.e.:
[mu kappa] = circ_vmpar(x)
vonmis = circ_randvm(mu,kappa,length(x))
Then I use the kuiper test to see whether the two distribution x and vonmis differ significantly (the difference can be in any property, such as mean, location and dispersion):
[H,pValue] = circ_kuipertest(x, vonmis)
However I was wondering if it is possible to have more accurate p-value estimates in the Kuiper test, as already asked by another user before.
thanks for your tip, however I'm not really convinced.
Both the circ_ktest and the circ_kuipertest are not described in the pdf:
Anyway, circ_ktest is a parametric two-sample test to determine whether two concentration parameters are different.
The circ_kuipertest is a two-sample test which allow to test whether two input samples differ significantly. The difference can be in any property, such as mean location and dispersion. It is a circular analogue of the Kolmogorov-Smirnov test.
I do not understand how these tests could help me with a goodness-of-fit test for the Von Mises-Fisher distribution, but probably is my limit.
Could anyone being of any help?
Hi guys, I'm new to circular statistics and I've downloaded this package.
Given some vectors, I'd like to test if they are distributed following a Von Mises-Fisher distribution.
Do you know what instructions of the package I should use?
Can you help?