origin_multiple: Multiple origin estimation using community partitioning

In NetOrigin: Origin Estimation for Propagation Processes on Complex Networks

Multiple origin estimation using community partitioning

Description

Multiple origin estimation using community partitioning

Usage

origin_multiple(
  events,
  type = c("edm", "backtracking", "centrality"),
  graph,
  no = 2,
  distance,
  fast = TRUE,
  ...
)

Arguments

events	numeric vector of event counts at specific time point
type	character specifying the method, 'edm', 'backtracking' and 'centrality' are available.
graph	igraph object specifying the underlying network graph
no	numeric specifying the number of supposed origins
distance	numeric matrix specifying the distance matrix
fast	logical specifying community partitioning algorithm, default is 'TRUE' that uses fastgreedy.community, 'FALSE' refers to leading.eigenvector.community
...	parameters to be passed to origin methods origin_edm, origin_backtracking or origin_centrality

Value

origin_multiple returns an list object with objects of class origin of length no

References

Zang, W., Zhang, P., Zhou, C. and Guo, L. (2014) Discovering Multiple Diffusion Source Nodes in Social Networks. Procedia Computer Science, 29, 443-452. <DOI: 10.1016/j.procs.2014.05.040>

See Also

Other origin-est: origin()

NetOrigin documentation built on Sept. 8, 2023, 5:58 p.m.