Simple form provided by WHuber: What is the distribution of the diameter of n points in the plane drawn iid from a bivariate Normal distribution? (Diameter is the greatest distance among any pair of the points.)
Original long form: Given a Rayleigh process R($\sigma$) generating cartesian samples $X_i \in \Re^2$ — which is equivalent to a bivariate normal process with 0 correlation and both sigmas = $\sigma$ — what is the distribution of the Extreme Spread of n samples?
Extreme spread $\widehat{ES_n(\sigma)} \equiv \max\limits_{i, j \in n}|X_i - X_j|$
E[$ES_n(\sigma)$], and Pr($ES_n(\sigma)$ > a), seems like it should have a chi(n) distribution, but I am not good enough to derive the exact relationship.
I did find this paper from 1975 which on p.8 suggests as much, but which focuses on empirical solution instead of on the pure math. In contrast, I want to take the parameters of the distribution of X as given and find a formulaic distribution for ES.
I don't know whether order statistics for these distributions have closed forms, but if so perhaps we can express this in terms of the expected value of first and nth order statistics?
Any guidance appreciated!