`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: model name, number of rows, skew of row sums, number of columns, skew of column sums, and running time.
Specifically, this 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.
# NOT RUN {
fixed_probs <- fixedfill(davis)
# }
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