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Last data update: 2014.03.03

R: Generating simulated networks

create_sim_data

R Documentation

Generating simulated networks

Description

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

Usage

create_sim_data(mode = 1, sat_at = 10, alpha = 0.5, beta = 1, N = 200)

Arguments

`mode`	Integer. Indicates the attachment function to be used in generating the network. If mode == 1, the attachment function is A_k = k^α. If mode == 2, the attachment function is A_k = min(k,sat_at)^α. If mode == 3, the attachment function is A_k = α log (k)^β. Default value is 1.
`sat_at`	Integer. This is the saturation position sat_at in the attachment function A_k = min(k,sat_at)^α.
`alpha`	Numeric. If mode == 1, this is the attachment exponent in the attachment function A_k = k^α. If mode == 2, this is the attachment exponenet in the attachment function A_k = min(k,sat_at)^α. If mode == 3, this is the alpha in the attachment function A_k = α log (k)^β + 1.
`beta`	Numeric. This is the beta in the attachment function A_k = α log (k)^β + 1.
`N`	Integer. Number of nodes in the final network.

Value

An object of class mcPAFit.Sim containing the true network as well as the random-shuffled final snapshot together with the true timeline.

Author(s)

Thong Pham thongpham@thongpham.net

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 <- create_sim_data(N = 100)