GreedyICL: GreedyICL
In GreedySBTM: Greedy Stochastic Block Transition Models

Description Usage Arguments Value References See Also Examples

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

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

`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

`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.

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

GreedyInit, GreedyMerge, CollapseLabels.