DcSbm {greed} | R Documentation |
Degree Corrected Stochastic Block Model Prior class
Description
An S4 class to represent a Degree Corrected Stochastic Block Model.
Such model can be used to cluster graph vertex, and model a square adjacency matrix with the following generative model :
The individuals parameters allow to take into account the node degree heterogeneity.
These parameters have uniform priors over the simplex
ie.
.
These classes mainly store the prior parameters value
of this generative model.
The
DcSbm-class
must be used when fitting a simple Degree Corrected Stochastic Block Model whereas the DcSbmPrior-class
must be used when fitting a CombinedModels-class
.
Usage
DcSbmPrior(p = NaN, type = "guess")
DcSbm(alpha = 1, p = NaN, type = "guess")
Arguments
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", "undirected" or "guess", default to "guess") |
alpha |
Dirichlet prior parameter over the cluster proportions (default to 1) |
Value
a DcSbmPrior-class
object
a DcSbm-class
object
See Also
DcSbmFit-class
, DcSbmPath-class
Other DlvmModels:
CombinedModels
,
DcLbm
,
DiagGmm
,
DlvmPrior-class
,
Gmm
,
Lca
,
MoM
,
MoR
,
MultSbm
,
Sbm
,
greed()
Examples
DcSbmPrior()
DcSbmPrior(type = "undirected")
DcSbm()
DcSbm(type = "undirected")