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RMThreshold
View on CRAN: Click
here
Download and install RMThreshold package within the R console
Install from CRAN:
install.packages("RMThreshold")
Install from Github:
library("remotes")
install_github("cran/RMThreshold")
Install by package version:
library("remotes")
install_version("RMThreshold", "1.1")
Attach the package and use:
library("RMThreshold")
Maintained by
Uwe Menzel
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-06-21
Latest Update: 2016-06-23
Description:
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.
How to cite:
Uwe Menzel (2016). RMThreshold: Signal-Noise Separation in Random Matrices by using Eigenvalue Spectrum Analysis. R package version 1.1, https://cran.r-project.org/web/packages/RMThreshold
Previous versions and publish date:
1.0 (2016-06-21 11:00)
Other packages that cited RMThreshold R package
View RMThreshold citation profile
Other R packages that RMThreshold depends,
imports, suggests or enhances
Functions, R codes and Examples using
the RMThreshold R package
Some associated functions: RMThreshold-internal . RMThreshold-package . add.Gaussian.noise . create.rand.mat . rm.connections . rm.denoise.mat . rm.discard.zeros . rm.ev.density . rm.get.threshold . rm.matrix.validation . rm.show.plots . rm.spacing.distribution .
Some associated R codes: RMThreshold.R . Full RMThreshold package functions and examples
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