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In [[Random matrix|random matrix theory]], the '''Marchenko–Pastur distribution''', or '''Marchenko–Pastur law''', describes the [[asymptotic]] behavior of [[singular values]] of large rectangular [[random matrix|random matrices]].  The theorem is named after [[Ukraine|Ukrainian]] [[mathematicians]] [[Vladimir Marchenko]] and [[Leonid Pastur]] who proved this result in 1967.


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If <math>X</math> denotes a <math>M\times N</math> random matrix whose entries are independent identically distributed random variables with mean 0 and variance  <math>\sigma^2 < \infty</math>, let
 
: <math>Y_N = N^{-1} X X^T \, </math>
 
and let <math>\lambda_1,\, \lambda_2, \,\dots,\, \lambda_M</math> be the [[eigenvalue]]s of <math>Y_N</math> (viewed as [[random variable]]s)Finally, consider the random measure
 
: <math>\mu_M (A) = \frac{1}{M} \# \left\{ \lambda_j \in A \right\}, \quad A \subset \mathbb{R}. </math>
 
'''Theorem'''. Assume that <math>M,\,N \,\to\, \infty</math> so that the ratio <math>M/N \,\to\, \lambda \in (0, +\infty)</math>. Then <math>\mu_{M} \,\to\, \mu</math> (in [[Weak_topology#The_weak-.2A_topology|weak* topology]] in [[Convergence_in_distribution#Convergence_in_distribution|distribution]]), where
: <math>\mu(A) =\begin{cases} (1-\frac{1}{\lambda}) \mathbf{1}_{0\in A} + \nu(A),& \text{if } \lambda >1\\
\nu(A),& \text{if } 0\leq \lambda \leq 1,
\end{cases}
</math>
and
: <math>d\nu(x) = \frac{1}{2\pi \sigma^2 } \frac{\sqrt{(\lambda_{+} - x)(x - \lambda_{-})}}{\lambda x} \,\mathbf{1}_{[\lambda_{-}, \lambda_{+}]}\, dx</math>
with
: <math> \lambda_{\pm} = \sigma^2(1 \pm \sqrt{\lambda})^2. \, </math>
 
The Marchenko–Pastur law also arises as the [[free Poisson law]] in free probability theory, having rate <math>\lambda</math> and jump size <math>\alpha</math>.
 
==See also ==
* [[Wigner semicircle distribution]]
 
==References==
{{Reflist}}
*Götze, F and Tikhomirov, A. (2004) "Rate of convergence in probability to the Marchenko–Pastur law", ''Bernoulli'', 10 (3), 503&ndash;548. {{doi|10.3150/bj/1089206408}}
*Marchenko,V. A., Pastur, L. A. (1967)  "Distribution of eigenvalues for some sets of random matrices", ''Mat. Sb. (N.S.)'', 72(114):4, 507&ndash;536 {{doi|10.1070/SM1967v001n04ABEH001994}} [http://www.mathnet.ru/php/archive.phtml?wshow=paper&jrnid=sm&paperid=4101&option_lang=eng Link to free-access pdf of Russian version]
*Nica, A.; [[Roland Speicher|Speicher, R.]] (2006) ''Lectures on the Combinatorics of Free probability theory'', Cambridge Univ. Press  ISBN 0-521-85852-6 (pp.&nbsp;204, 368). [http://www.ebooksdownloadfree.com/Science-Technology/Lectures-on-the-Combinatorics-of-Free-Probability-BI9525.html Link to free download] [http://www.google.com/search?tbs=bks:1&q=isbn:0521858526 Another free access site]
{{ProbDistributions|continuous-semi-infinite}}
{{DEFAULTSORT:Marchenko-Pastur distribution}}
[[Category:Probability distributions]]
[[Category:Random matrices]]

Latest revision as of 15:24, 19 September 2013


In random matrix theory, 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 Vladimir Marchenko and Leonid Pastur who proved this result in 1967.

If X denotes a M×N random matrix whose entries are independent identically distributed random variables with mean 0 and variance σ2<, let

YN=N1XXT

and let λ1,λ2,,λM be the eigenvalues of YN (viewed as random variables). Finally, consider the random measure

μM(A)=1M#{λjA},A.

Theorem. Assume that M,N so that the ratio M/Nλ(0,+). Then μMμ (in weak* topology in distribution), where

μ(A)={(11λ)10A+ν(A),if λ>1ν(A),if 0λ1,

and

dν(x)=12πσ2(λ+x)(xλ)λx1[λ,λ+]dx

with

λ±=σ2(1±λ)2.

The Marchenko–Pastur law also arises as the free Poisson law in free probability theory, having rate λ and jump size α.

See also

References

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  • Götze, F and Tikhomirov, A. (2004) "Rate of convergence in probability to the Marchenko–Pastur law", Bernoulli, 10 (3), 503–548. 21 year-old Glazier James Grippo from Edam, enjoys hang gliding, industrial property developers in singapore developers in singapore and camping. Finds the entire world an motivating place we have spent 4 months at Alejandro de Humboldt National Park.
  • Marchenko,V. A., Pastur, L. A. (1967) "Distribution of eigenvalues for some sets of random matrices", Mat. Sb. (N.S.), 72(114):4, 507–536 21 year-old Glazier James Grippo from Edam, enjoys hang gliding, industrial property developers in singapore developers in singapore and camping. Finds the entire world an motivating place we have spent 4 months at Alejandro de Humboldt National Park. Link to free-access pdf of Russian version
  • Nica, A.; Speicher, R. (2006) Lectures on the Combinatorics of Free probability theory, Cambridge Univ. Press ISBN 0-521-85852-6 (pp. 204, 368). Link to free download Another free access site

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