tauInitial: List of initial values for tau

In ppsbm: Clustering in Longitudinal Networks

Description

Same function whatever directed or undirected case

Usage

tauInitial(data, n, Q, d_part, n_perturb, perc_perturb, n_random, directed)

Arguments

data	Data : only needs the N_{ijk} field of data
n	Total number of nodes
Q	Total number of groups
d_part	Maximal level for finest partitions of time interval [0,T], used for kmeans initializations. Algorithm takes partition up to depth 2^d with d=1,...,d_{part} Explore partitions [0,T], [0,T/2], [T/2,T], ... [0,T/2^d], ...[(2^d-1)T/2^d,T] Total number of partitions npart= 2^{(d_part +1)} - 1
n_perturb	Number of different perturbations on k-means result
perc_perturb	Percentage of labels that are to be perturbed (= randomly switched)
n_random	Number of completely random initial points. If not zero there will be n_random taus uniformly sampled in the initialization.
directed	Boolean for directed (TRUE) or undirected (FALSE) case

Details

The (maximal) total number of initializations is d_{part}*(1+n_{perturb}) + n_{random}

Value

List of matrixes of initial values for τ

Examples

# Generate initial tau for generated_Q3 data

n <- 50
Dmax <- 2^3
Q <- 3
d_part <- 1 # less than 3 (owing to Dmax)
n_perturb <- 2
perc_perturb <- 0.2
n_random <- 1
directed <- FALSE

data <- list(Nijk = statistics(generated_Q3$data, n, Dmax, directed = FALSE))

tau <- tauInitial(data,n,Q,d_part,n_perturb,perc_perturb,n_random,directed)

ppsbm documentation built on May 1, 2019, 11:26 p.m.