GreedySBTM (version 1.0)

GreedyICL: GreedyICL

Description

Runs the GreedyICL algorithm on the provided network to maximise the exact integrated complete likelihood.

Usage

GreedyICL(adj_cube, allocations, max_n_iter = 100, verbose = FALSE)

Arguments

adj_cube

A binary array of size NxNxT representing the dynamic network. The generic entry in position [i,j,t] is equal to 1 if i interacts with j during the t-th time frame, or to 0 otherwise. Only undirected networks with no self-edges are supported, so each slice of the array must be a symmetric matrix with null elements on the diagonal.

allocations

Initial allocations used by the greedy algorithm. This should be a matrix of size TxN denoting the cluster membership of each node at each time. Values should be strictly positive integers. The value zero should be used to identify inactive nodes.

max_n_iter

A positive integer denoting the maximum number of iterations for the GreedyICL maximisation. Defaults to 100 (i.e. each node is updated up to 100 times).

verbose

TRUE or FALSE, indicating whether a lenghty output should be printed out. Defaults to FALSE

Value

computing_time

Number of seconds required to perform the optimisation.

icl_start

Exact log-ICL value for the initial allocations.

icl_trace

Exact log-ICL values for each of the solutions visited during the optimisation.

icl_end

Exact log-ICL value for the optimal allocations found.

allocations

Optimal allocations.

References

Rastelli, R. (2017) "Exact integrated completed likelihood maximisation in a stochastic block transition model for dynamic networks", https://arxiv.org/abs/1710.03551

See Also

GreedyInit, GreedyMerge, CollapseLabels.

Examples

# NOT RUN {
### A complete example is provided in the documentation of GreedyMerge.
# }