single_unbiased_random_walker: Implementation of voter model dynamics on a network in R.

In Fagan-Lab/dynet: Network Dynamics

Description

Simulate voter-model-style dynamics on a network. Nodes are randomly assigned a state in (-1,1) at each time step all nodes asynchronously update by choosing their new state uniformly from their neighbors. Generates an N*L time series. The results dictionary also stores the time series as TS and ground truth adjacency matrix as ground_truth.

Usage

single_unbiased_random_walker(input_matrix, L, initial_node = NULL)

Arguments

input_matrix	the input (ground-truth) graph with N nodes. Must be valid square adjacency matrix.
L	the length of the desired time series.
initial_node	starting node for walk

Value

results a list with TS matrix an N*L array of synthetic time series data.

Fagan-Lab/dynet documentation built on March 3, 2021, 2:53 a.m.