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EigenvalueSpreadsForRandomMatrices

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Function Description

Returns the (sorted) values of  (containing  terms) above which we would not expect eigenvalues to lie if coming from a covariance matrix derived from samples of independent, identically distributed (Gausssian) random variables, if the number of variables,  is large, given an array of actual observed eigenvalues and given the number of observations applicable to each underlying variable.

 

See Random Matrix Theory for further details.

 


Links to:

-          Interactively run function

-          Interactive instructions

-          Example calculation

-          Output type / Parameter details

-          Illustrative spreadsheet

-          Other Risk management functions

-          Computation units used


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