# tauInitial: List of initial values for tau In ppsbm: Clustering in Longitudinal Networks

## Description

Same function whatever directed or undirected case

## Usage

 `1` ```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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```# 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.