Papers › Another Marčenko-Pastur law for Kendall's tau
Another Marčenko-Pastur law for Kendall's tau
Pierre Bousseyroux, Tomas Espana, Matteo Smerlak
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Bandeira et al. (2017) show that the eigenvalues of the Kendall correlation matrix of n i.i.d. random vectors in ℝᵖ are asymptotically distributed like 1/3 + (2/3)Y_q, where Y_q has a Mar\v{c}enko-Pastur law with parameter q=lim(p/n) if p, n→∞ proportionately to one another. Here we show that another Mar\v{c}enko-Pastur law emerges in the "ultra-high dimensional" scaling limit where p∼q′ n²/2 for some q′>0: in this quadratic scaling regime, Kendall correlation eigenvalues converge weakly almost surely to (1/3)Y_(q′).
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections