RMThreshold: Signal-Noise Separation in Random Matrices by using Eigenvalue Spectrum Analysis
Version 1.1

An algorithm which can be used to determine an objective threshold for signal-noise 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

AuthorUwe Menzel
Date of publication2016-06-23 19:57:40
MaintainerUwe Menzel <[email protected]>
LicenseGPL
Version1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("RMThreshold")

Try the RMThreshold package in your browser

Any scripts or data that you put into this service are public.

RMThreshold documentation built on May 29, 2017, 11 p.m.