Constructing networks by filtering correlation matrices: a null model approach

DOI10.1098/rspa.2019.0578zbMath1472.92115arXiv1903.10805OpenAlexW3100581340WikidataQ91866728 ScholiaQ91866728MaRDI QIDQ5160819

Naoki Masuda, Sadamori Kojaku

Publication date: 29 October 2021

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1903.10805

zbMATH Keywords

statistical physicsthresholdingprinciple of maximum entropystatisticssparsityLassonetwork inference

Mathematics Subject Classification ID

Systems biology, networks (92C42) Biological rhythms and synchronization (92B25)

Related Items (1)

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Uses Software

• Adam
• config_corr

Cites Work

• Sparse estimation of a covariance matrix
• Sparse inverse covariance estimation with the graphical lasso
• The Adaptive Lasso and Its Oracle Properties
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• Network exploration via the adaptive LASSO and SCAD penalties
• What you export matters
• Extended Bayesian information criteria for model selection with large model spaces
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Networks
• Theory of Financial Risk and Derivative Pricing
• Tuning Parameter Selection for the Adaptive Lasso Using ERIC
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