BipartiteSBM_fit {sbm} | R Documentation |
R6 Class definition of an Bipartite SBM fit
Description
R6 Class definition of an Bipartite SBM fit
R6 Class definition of an Bipartite SBM fit
Details
This class is designed to give a representation and adjust an LBM fitted with blockmodels.
Super classes
sbm::SBM
-> sbm::BipartiteSBM
-> BipartiteSBM_fit
Active bindings
loglik
double: approximation of the log-likelihood (variational lower bound) reached
ICL
double: value of the integrated classification log-likelihood
penalty
double, value of the penalty term in ICL
entropy
double, value of the entropy due to the clustering distribution
storedModels
data.frame of all models fitted (and stored) during the optimization
Methods
Public methods
Inherited methods
Method new()
constructor for a Bipartite SBM fit
Usage
BipartiteSBM_fit$new( incidenceMatrix, model, dimLabels = c(row = "row", col = "col"), covarList = list() )
Arguments
incidenceMatrix
rectangular (weighted) matrix
model
character (
'bernoulli'
,'poisson'
,'gaussian'
)dimLabels
labels of each dimension (in row, in columns)
covarList
and optional list of covariates, each of whom must have the same dimension as
incidenceMatrix
Method optimize()
function to perform optimization
Usage
BipartiteSBM_fit$optimize(estimOptions = list())
Arguments
estimOptions
a list of parameters controlling the inference algorithm and model selection. See details.
Method setModel()
method to select a specific model among the ones fitted during the optimization. Fields of the current SBM_fit will be updated accordingly.
Usage
BipartiteSBM_fit$setModel(index)
Arguments
index
integer, the index of the model to be selected (row number in storedModels)
Method reorder()
permute group labels by order of decreasing probability
Usage
BipartiteSBM_fit$reorder()
Method show()
show method
Usage
BipartiteSBM_fit$show(type = "Fit of a Bipartite Stochastic Block Model")
Arguments
type
character used to specify the type of SBM
Method clone()
The objects of this class are cloneable with this method.
Usage
BipartiteSBM_fit$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.