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tauInitial

List of initial values for τ

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

Clustering in Longitudinal Networks

v0.2.2
GPL (>= 2)
Authors
D. Giorgi, C. Matias, T. Rebafka, F. Villers
Initial release

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