Document Detail

Spectral properties of empirical covariance matrices for data with power-law tails.
MedLine Citation:
PMID:  17155044     Owner:  NLM     Status:  PubMed-not-MEDLINE    
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.
Zdzisław Burda; Andrzej T Görlich; Bartłomiej Wacław
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Publication Detail:
Type:  Journal Article     Date:  2006-10-31
Journal Detail:
Title:  Physical review. E, Statistical, nonlinear, and soft matter physics     Volume:  74     ISSN:  1539-3755     ISO Abbreviation:  Phys Rev E Stat Nonlin Soft Matter Phys     Publication Date:  2006 Oct 
Date Detail:
Created Date:  2006-12-12     Completed Date:  2007-01-11     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101136452     Medline TA:  Phys Rev E Stat Nonlin Soft Matter Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  041129     Citation Subset:  -    
Mark Kac Center for Complex Systems Research and Marian Smoluchowski Institute of Physics, Jagellonian University, Reymonta 4, 30-059 Krakow, Poland.
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