This function uses an envelope-rejection method based on a wrapped Cauchy distribution to draw random variates from an arbitrary Von Mises distribution, first proposed in .
'fMu' and 'fKappa' are the mean and variance parameter of the Von Mises distribution over [-pi, pi). 'tVMVariates' will be a tensor containing random variates drawn from the defined distribution. If 'fMu' and 'fKappa' are non-scalar, then they must be the same size. In this case 'tVMVariates' will be the same size. If 'fMu' and 'fKappa' are scalar, then the number of variates returned can be specified as extra arguments.
vmrand(linspace(-pi, pi, 20), 2); % - Return variates for several distributions, with changing 'fMu'
vmrand(0, 2, [100 1]); % - Return 100 variates (size [100 1]) for the VM distribution with 'fMu' = 0 and 'fKappa' = 2
If only single dimension 'M' is provided, then the return argument 'tfVMVariates' will be M x M.
This implementation is vectorised, and requires O(7.5*N) space.
 D. J. Best and N. I. Fisher, 1979. "Efficient Simulation of the von Mises Distribution", Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 28, No. 2, pp. 152-157.
Dylan Muir (2022). vmrand(fMu, fKappa, varargin) (https://www.mathworks.com/matlabcentral/fileexchange/37241-vmrand-fmu-fkappa-varargin), MATLAB Central File Exchange. Retrieved .
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