`fixedfill` computes the probability of observing
a higher or lower edge weight.
Once computed, use backbone.extract to return
the backbone matrix for a given alpha value.
fixedfill(B)graph: An unweighted bipartite graph object of class matrix, sparse matrix, igraph, edgelist, or network object. Any rows and columns of the associated bipartite matrix that contain only zeros are automatically removed before computations.
backbone, a list(positive, negative, summary). Here `positive` is a matrix of probabilities of edge weights being equal to or above the observed value in the projection, `negative` is a matrix of probabilities of edge weights being equal to or below the observed value in the projection, and `summary` is a data frame summary of the inputted matrix and the model used including: class, model name, number of rows, number of columns, and running time.
The fixedfill function compares an edge's observed weight in the projection \(B*t(B)\) to the distribution of weights expected in a projection obtained from a random bipartite graph where the number of edges present is equal to the number of edges in B. When B is large, this function may be impractically slow and may return a backbone object that contains NaN values.
Neal, Domagalski, and Sagan. 2021. "Comparing Models for Extracting the Backbone of Bipartite Projections." arXiv:2105.13396 cs.SI)
# NOT RUN {
fixed_probs <- fixedfill(davis)
# }
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