I am interested in comparing the amount of variability within 8 different samples (each from a different population). I am aware that this can be done by several methods with ratio data: F-test equality of variance, Levene test, etc.
However, my data is circular/directional (i.e. data that exhibit periodicity such as wind direction and in general angular data, or time of the day). I have done some research and found one test in the "CircStats" package in R - "Watson's test for homogeneity". One shortcoming is that this test only compares two samples, which means I would have to do multiple comparisons on my 8 samples (and then use the Bonferonni correction).
Here are my questions:
1) Is there a better test that I can use?
2) If not, what are the assumptions of Watson's test? Is it parametric/non-parametric?
3) What is the algorithm by which I can perform this test? My data is in Matlab, and I would prefer to not have to transfer it into R to run my test. I'd rather just write my own function.