# bipartite.from.distribution: Generates a bipartite network with given row and column... In backbone: Extracts the Backbone from Weighted Graphs

## Description

'bipartite.from.distribution' returns a bipartite graph, as an object of the requested class, with row and column degree distributions that approximately follow beta distributions with given parameters.

## Usage

 ```1 2 3 4 5 6 7 8``` ```bipartite.from.distribution( R, C, P, rowdist = c(1, 1), coldist = c(1, 1), class = "matrix" ) ```

## Arguments

 `R` integer: number of rows `C` integer: number of columns `P` numeric: probability of an edge `rowdist` vector length 2: Row degrees will approximately follow a Beta(a,b) distribution `coldist` vector length 2: Column degrees will approximately follow a Beta(a,b) distribution `class` string: the class of the returned backbone graph, one of c("matrix", "Matrix", "sparseMatrix", "igraph", "network")

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```B <- bipartite.from.distribution(R = 100, C = 100, P = 0.1, rowdist = c(1,1), coldist = c(1,1)) #Uniform B <- bipartite.from.distribution(R = 100, C = 100, P = 0.1, rowdist = c(1,10), coldist = c(1,10)) #Right-tailed B <- bipartite.from.distribution(R = 100, C = 100, P = 0.1, rowdist = c(10,1), coldist = c(10,1)) #Left-tailed B <- bipartite.from.distribution(R = 100, C = 100, P = 0.1, rowdist = c(10,10), coldist = c(10,10)) #Normal B <- bipartite.from.distribution(R = 100, C = 100, P = 0.1, rowdist = c(10000,10000), coldist = c(10000,10000)) #Constant ```

backbone documentation built on Sept. 18, 2021, 1:07 a.m.