| SimpleSBM_fit {sbm} | R Documentation |
R6 Class definition of a Simple SBM fit
Description
R6 Class definition of a Simple SBM fit
R6 Class definition of a Simple SBM fit
Details
This class is designed to give a representation and adjust an SBM fitted with blockmodels.
Super classes
sbm::SBM -> sbm::SimpleSBM -> SimpleSBM_fit
Active bindings
loglikdouble: approximation of the log-likelihood (variational lower bound) reached
ICLdouble: value of the integrated classification log-likelihood
penaltydouble, value of the penalty term in ICL
entropydouble, value of the entropy due to the clustering distribution
storedModelsdata.frame of all models fitted (and stored) during the optimization
Methods
Public methods
Inherited methods
Method new()
constructor for a Simple SBM fit
Usage
SimpleSBM_fit$new( adjacencyMatrix, model, directed, dimLabels = c(node = "nodeName"), covarList = list() )
Arguments
adjacencyMatrixsquare (weighted) matrix
modelcharacter (
'bernoulli','poisson','gaussian')directedlogical, directed network or not. In not,
adjacencyMatrixmust be symmetric.dimLabelslist of labels of each dimension (in row, in columns)
covarListand optional list of covariates, each of whom must have the same dimension as
adjacencyMatrix
Method optimize()
function to perform optimization
Usage
SimpleSBM_fit$optimize(estimOptions = list())
Arguments
estimOptionsa 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
SimpleSBM_fit$setModel(index)
Arguments
indexinteger, the index of the model to be selected (row number in storedModels)
Method reorder()
permute group labels by order of decreasing probability
Usage
SimpleSBM_fit$reorder()
Method show()
show method
Usage
SimpleSBM_fit$show(type = "Fit of a Simple Stochastic Block Model")
Arguments
typecharacter used to specify the type of SBM
Method clone()
The objects of this class are cloneable with this method.
Usage
SimpleSBM_fit$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.