Iterative procedure for network inference

Gloria Cecchini*, Bjoern Schelter

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

When a network is reconstructed from data, two types of errors can occur: false positive and false negative errors about the presence or absence of links. In this paper, the vertex degree distribution of the true underlying network is analytically reconstructed using an iterative procedure. Such procedure is based on the inferred network and estimates for the probabilities α and β of type I and type II errors, respectively. The iteration procedure consists of choosing various values for α to perform the iteration steps of the network reconstruction. For the first step, the standard value for α of 0.05 can be chosen as an example. The result of this first step gives a first estimate of the network topology of interest. For the second iteration step the value for α is adjusted according to the findings of the first step. This procedure is iterated, ultimately leading to a reconstruction of the vertex degree distribution tailored to its previously unknown network topology.
Original language English 105286 10 Communications in Nonlinear Science & Numerical Simulation 88 28 Apr 2020 https://doi.org/10.1016/j.cnsns.2020.105286 Published - Sep 2020

Keywords

• network inference
• node degree distribution
• false positive
• false negative
• statistical inference
• False positive
• Node degree distribution
• Network inference
• Statistical inference
• MINIMUM DISTANCE
• COMPLEX NETWORKS