Thanks people, this toolbox is really helpful and easy to use.

I have one stats question -- forgive me that it is not a direct question about this toolbox but perhaps someone could help nonetheless.

I have repeated measures of circular data for multiple participants, lets say 15 participants where each participant contributes four angles. I have reason to believe that the angular distributions are going to be multipolar and not von Mises distributed. This would in essence require some kind of non-parametric repeated measures test which I am not sure has been developed for circular data. Is there a way to test for circular uniformity in this data set by using the procedures in the circstat toolbox, perhaps using some kind of p-value correction?

On a quick look, the Moore-Rayleigh test for uniformity of vector data (B.R. Moore, Biometrika, 1980) does not seem to be available in this toolbox. Philipp, do you have any plans to implement it? Alternatively, does anyone know if a Matlab implementation of that test is available elsewhere? Thanks.

Hi everybody!
I have a question about circ_plot.m; When I execute this code the angles appear from 0 to 360 degrees.
I only want represent values from 0 to 180. How I can do it? Thanks in advance!

Actually, ignore the inverse_cdf function I have provided. It should generate a vlaue for kappa and it needs adjusting for values of thetahat other than zero.

Great submission. It would be nice to have cdf and inversion cdf for the vmpdf functions. Here's what I wrote for my needs
function p = circ_vmcdf(alpha, thetahat, kappa)
%integrates the pdf from an angle of -pi to an angle alpha
F = @(x)circ_vmpdf(x, thetahat, kappa);
p = quad(F,-pi(),alpha);
end
function theta = circ_vminv(p, thetahat, kappa)
%computes the inverse of the abovecirc_vmcdf.
fun =@(alpha)(circ_vmcdf(alpha, thetahat, kappa)-p);
theta = fzero(fun,[-pi pi]);
end

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