An algorithm which can be used to determine an objective threshold for signalnoise separation in large random matrices (correlation matrices, mutual information matrices, network adjacency matrices) is provided. The package makes use of the results of Random Matrix Theory (RMT). The algorithm increments a suppositional threshold monotonically, thereby recording the eigenvalue spacing distribution of the matrix. According to RMT, that distribution undergoes a characteristic change when the threshold properly separates signal from noise. By using the algorithm, the modular structure of a matrix  or of the corresponding network  can be unraveled.
Package details 


Author  Uwe Menzel 
Maintainer  Uwe Menzel <[email protected]> 
License  GPL 
Version  1.1 
Package repository  View on CRAN 
Installation 
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