simple_net: Generating simulated networks

In mcPAFit: Estimating Preferential Attachment from a Single Network Snapshot by Markov Chain Monte Carlo

Description

This function generates a complex network from the Barabasi-Albert model and a random order to create a random network.

Usage

simple_net(time_step, 
           num_seed           = 2     , 
           p                  = 0.5   ,
           alpha              = 1     ,
           alpha_out          = 0   )

Arguments

time_step	Integer. Indicates the number of time-steps.
num_seed	Integer. Number of nodes in the initial network.
p	Numeric. Proportion of number of nodes.
alpha	Numeric. The attachment exponent for the in-degree.
alpha_out	Numeric. The attachment exponent for the out-degree.

Value

An three-column matrix containing the generated network.

Author(s)

Thong Pham [e-mail]

References

1. Pham, T. and Sheridan, P. and Shimodaira, H. (2015). mcPAFit: Nonparametric Measurement of Preferential Attachment and Fitness from a Single Network Snapshot. Conference on Complex Systems 2015, September 2015, Arizona.

Examples

library("mcPAFit")
data <- simple_net(100) # Time-steps = 100

mcPAFit documentation built on May 2, 2019, 11:42 a.m.