Synthetic matrix ensemble for nestedness analysis

Ten replicates of the initial 500 matrices were made for each rewiring level. The entire ensemble is then 500x10x6 = 30,000 networks. Each of these 30,000 networks was then analysed for nestedness using FALCON (Beckett et al., 2014).

Six nestedness measures and five null models were used. Details of these analyses can be found in Beckett and Williams (submitted). The dataset contains: code: MATLAB code used to create the synthetic ensemble. - SHAPE_MATRIX.m a MATLAB function for creating a 'perfectly nested' bipartite network with given rows, columns and curvature parameters. - makeBenchmarkEnsemble.m a MATLAB function for creating a set of X matrices rewired from an initial matrix with probability P. - randomiseMatrix.m a MATLAB function for rewiring a given input matrix with probability P. networks: The set of networks used in the synthetic ensemble. - A total of 30,000 binary matrices each saved as a separate csv file. output: The output data from nestedness analysis for each measure. - Five csv files corresponding to output from the five null models used (SS,FF,CC,DD,EE). - For each measure (NODF, MD, SR, JDM, BR, NTC) the measure score, p-value, z-score and adjusted normalised temperature(AnT) scores are given.

Beckett S.J., Williams H.T.P. Brooding on nestedness: nestedness analyses are confounded by sensitivity to measurement choices and network properties. submitted. Beckett SJ, Boulton CA and Williams HTP. FALCON: a software package for analysis of nestedness in bipartite networks [v1; ref status: indexed, f1000r.es/3z8] F1000Research 2014, 3:185 (doi: 10.12688/f1000research.4831.1)