An S4 class to represent a degree corrected stochastic block model, extend icl_model-class. Such model can be used to cluster graph vertex, and model a square adjacency matrix $$X$$ with the following generative model : $$\pi \sim Dirichlet(\alpha)$$ $$Z_i \sim \mathcal{M}(1,\pi)$$ $$\theta_{kl} \sim Exponential(p)$$ $$\gamma_i^+,\gamma_i^- \sim \mathcal{U}(S_k)$$ $$X_{ij}|Z_{ik}Z_{jl}=1 \sim \mathcal{P}(\gamma_i^+\theta_{kl}\gamma_j^-)$$ The individuals parameters $$\gamma_i^+,\gamma_i^-$$ allow to take into account the node degree heterogeneity. These parameters have uniform priors over the simplex $$S_k$$ ie. $$\sum_{i:z_{ik}=1}\gamma_i^+=1$$. This class mainly store the prior parameters value $$\alpha$$ of this generative model in the following slots (the prior parameter $$p$$ is estimated from the data as the global average probability of connection between two nodes):

## Slots

name

name of the model

alpha

Dirichlet over cluster proportions prior parameter (default to 10)

p

Exponential prior parameter (default to NaN, in this case p will be estimated from data as the mean connection probability)

type

define the type of networks (either "directed" or "undirected", default to "directed")