compute a list of initial points of tau and rhofor the VEM algorithm for a given number of blocks; returns nbOfTau*nbOfPointsPerTau inital points
initialPoints(
Q,
dataMatrix,
nbOfTau,
nbOfPointsPerTau,
modelFamily,
model,
directed
)number of latent blocks in the noisy stochastic block model
observed dense adjacency matrix
number of initializations for the latent block memberships
number of initializations of the latent binary graph associated with each initial latent block memberships
probability distribution for the edges. Possible values:
Gauss, Gamma
Implemented models:
Gaussall Gaussian parameters of the null and the alternative distributions are unknown ; this is the Gaussian model with maximum number of unknown parameters
Gauss0compared to Gauss, the mean of the null distribution is set to 0
Gauss01compared to Gauss, the null distribution is set to N(0,1)
GaussEqVarcompared to Gauss, all Gaussian variances (of both the null and the alternative) are supposed to be equal, but unknown
Gauss0EqVarcompared to GaussEqVar, the mean of the null distribution is set to 0
Gauss0Var1compared to Gauss, all Gaussian variances are set to 1 and the null distribution is set to N(0,1)
Gauss2distrthe alternative distribution is a single Gaussian distribution, i.e. the block memberships of the nodes do not influence on the alternative distribution
GaussAffilcompared to Gauss, for the alternative distribution, there's a distribution for inter-group and another for intra-group interactions
Expthe null and the alternatives are all exponential distributions (i.e. Gamma distributions with shape parameter equal to one) with unknown scale parameters
ExpGammathe null distribution is an unknown exponential, the alterantive distribution are Gamma distributions with unknown parameters
booelan to indicate whether the model is directed or undirected
list of inital points of tau and rho of length nbOfTau*nbOfPointsPerTau