distribution-free

On traditional statistics, I voted with my research and did work that was distribution-free, also multidimensional, unusual for distribution-free.

It has nothing to do with any Gaussian distribution (is distribution-free), principal components analysis, singular value decomposition, etc.

So, have a statistical hypothesis test that is both multi-dimensional and distribution-free, one of the first such.

There is a long history of hypothesis tests for from a single variable, including many tests that are distribution-free.

Also for such multi-variate data can't hope to know any of the probability distributions so need tests that are distribution-free.

So, how many multi-dimensional, distribution-free statistical hypothesis tests did you find in the library?

I have yet to see a distribution-free test that tries to argue it is as powerful as Neyman-Pearson!

It turns out, we don't need to say anything about that distribution because we are being 'distribution-free'.

So, we would like a detector that is distribution-free, that is, makes no assumptions about probability distributions.

Here we have an introduction to distribution-free, that is, 'non-parametric', hypothesis testing based on ranks or permutations.

For multi-dimensional hypothesis tests, there's not much and still less when also distribution-free.

So, we would get multidimensional, distribution-free 'behavioral monitoring' with false alarm rate we could set in advance and get exactly.