RMThreshold
1.1Signal-Noise Separation in Random Matrices by using Eigenvalue Spectrum Analysis
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 82%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- References docs
- 33%
Downloads
Dependencies
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Code & Tests
People & History
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 1.1Latest
- 1.02016-06-21
- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-06-21
- Total releases
- 2 / 10 yrs
- License
- GPL
- Download size
- 537 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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