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Spectral properties of empirical covariance matrices for data with power-law tails
We present an analytic method for calculating spectral densities of empirical
covariance matrices for correlated data. In this approach the data is
represented as a rectangular random matrix whose columns correspond to sampled
states of the system. The method is applicable to a class of random matrices
with radial measures including those with heavy (power-law) tails in the
probability distribution. As an example we apply it to a multivariate Student
distribution.Comment: 9 pages, 3 figures, references adde
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