simulation_instance: Shuffling Simulation of different graph models

In dpmcsuss/gmmle:

Description

Run a simulation instance of different graph models by shuffling vertices and computing disagreement statistics. Models include Erdos Renyi (ER), Watts-Strogatz small world graphs with rewiring probabilities of 0.05 and 0.7, and preferential attachment (PA) models with powers of 1, 1, and 2, and zero.appeal of 0, 500, and 0. All graphs are undirected with n=500 vertices. Each graph is sampled once and the shuffles are repeated m times.

Usage

simulation_instance(
  k_grid = c(2, 10, 50, 100, 200, 400),
  d = 1,
  seed = 0,
  m = 1000,
  n = 500,
  ask = TRUE
)

Arguments

k_grid	sequence of values for number of shuffled vertices
d	average degree of the random graph seed = random seed
seed	Seed for random number generator
m	number of Monte Carlo replicates
n	number of nodes
ask	Ask about running big simulations.

Value

Tibble with rows for each graph-K pair and 7 columns, one for the model, parameters, and K. Columns 4:6 give the mean, sd, and min for the number of edge disagreements. Column 7 gives a theoretical estimate for the maximum probability of edge flips for which graph matching will still be possible.

Examples

 simulation_instance(k_grid = c(2, 10),
   m = 10, n = 30, ask = FALSE)

dpmcsuss/gmmle documentation built on July 2, 2020, 6:24 p.m.