Construct · 1 fields · 1 citations

Marchenko-Pastur law: a standalone construct

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Random matrix theory

the limiting eigenvalue distribution of large sample covariance matrices, used to separate signal from noise in high-dimensional data.

In random matrix theory, Marchenko-Pastur law refers to the limiting eigenvalue distribution of large sample covariance matrices, used to separate signal from noise in high-dimensional data. This meaning comes from Marčenko (1967) in Mathematics of the USSR-Sbornik.[1]

Unit
Recovery means
Measured by

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Nearby constructs

covariance3 fields · 3 citationsjingle · one word, three constructs distribution2 fields · 2 citationsjingle · one word, two constructs matrix3 fields · 4 citationsjingle · one word, three constructs

References

Marčenko, V. A., & Pastur, L. A. (1967). Distribution of Eigenvalues for Some Sets of Random Matrices. Mathematics of the USSR-Sbornik, 1(4), 457-483. https://doi.org/10.1070/sm1967v001n04abeh001994

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