Marchenko–Pastur distribution
Distribution of singular values of large rectangular random matrices / From Wikipedia, the free encyclopedia
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In the mathematical theory of random matrices, the Marchenko–Pastur distribution, or Marchenko–Pastur law, describes the asymptotic behavior of singular values of large rectangular random matrices. The theorem is named after Ukrainian mathematicians Volodymyr Marchenko and Leonid Pastur who proved this result in 1967.
If denotes a random matrix whose entries are independent identically distributed random variables with mean 0 and variance , let
and let be the eigenvalues of (viewed as random variables). Finally, consider the random measure
counting the number of eigenvalues in the subset included in .
Theorem. [citation needed] Assume that so that the ratio . Then (in weak* topology in distribution), where
and
with
The Marchenko–Pastur law also arises as the free Poisson law in free probability theory, having rate and jump size .