DcLbm {greed} | R Documentation |
Degree Corrected Latent Block Model for bipartite graph class
Description
An S4 class to represent a degree corrected stochastic block model for co_clustering of bipartite graph.
Such model can be used to cluster graph vertex, and model a bipartite graph 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 simplex
.
These classes mainly store the prior parameters value
of this generative model.
The
DcLbm-class
must be used when fitting a simple Diagonal Gaussian Mixture Model whereas the DcLbmPrior-class
must be sued when fitting a CombinedModels-class
.
Usage
DcLbmPrior(p = NaN)
DcLbm(alpha = 1, p = NaN)
Arguments
p |
Exponential prior parameter (default to Nan, in this case p will be estimated from data as the average intensities of X) |
alpha |
Dirichlet prior parameter over the cluster proportions (default to 1) |
Value
a DcLbmPrior-class
a DcLbm-class
object
See Also
DcLbmFit-class
, DcLbmPath-class
Other DlvmModels:
CombinedModels
,
DcSbm
,
DiagGmm
,
DlvmPrior-class
,
Gmm
,
Lca
,
MoM
,
MoR
,
MultSbm
,
Sbm
,
greed()
Examples
DcLbmPrior()
DcLbmPrior(p = 0.7)
DcLbm()
DcLbm(p = 0.7)