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Data from: Measuring nestedness: a comparative study of the performance of different metrics

Citation

Payrató Borràs, Clàudia; Hernández, Laura; Moreno, Yamir (2021), Data from: Measuring nestedness: a comparative study of the performance of different metrics, Dryad, Dataset, https://doi.org/10.5061/dryad.bk3j9kd8b

Abstract

Nullnest

The nullnest repository provides a set of programs developed for constructing a null model of bipartite networks which constraints the degree sequences -on average-, along with the measurement of the degree of nestedness of bipartite networks using a large variety of metrics allowing for the comparison of this value against the null expectation. The whole repository is documented and maintained at: https://github.com/cclaualc/nullnest.

The package is divided into two main blocks. On the one hand, we provide a program to compute the null model, for any bipartite network introduced by the user, which keeps the original degree sequence constant on average while maximizing the entropy of the null ensemble. We also give the ready-to-use results of the null model for an important number of real networks available online. On the other hand, the package contains the programs to measure the degree of nestedness of any network, measuring as well the first two moments of its null distribution, either by using analytical expressions or by numerically sampling the null ensemble.

For more information on the functioning, modificable options, implementation and references of this repository visit the github link. When using these programs please acknowledge the authors.

Usage Notes

To use these files, take a look at the ReadMe file or check the updated github repository: https://github.com/cclaualc/nullnest

Funding

Ministerio de Economía y Competitividad

European Regional Development Fund, Award: FIS2017-87519-P

Government of Aragón

LABEX MME-DII, Award: ANR reference 11-LABX-0023