R6 Class definition of an Bipartite SBM fit
R6 Class definition of an Bipartite SBM fit
R6 Class definition of an Bipartite SBM fit
This class is designed to give a representation and adjust an LBM fitted with blockmodels.
sbm::SBM -> sbm::BipartiteSBM -> BipartiteSBM_fit
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
new()constructor for a Bipartite SBM fit
BipartiteSBM_fit$new(
incidenceMatrix,
model,
dimLabels = c(row = "row", col = "col"),
covarList = list()
)
incidenceMatrix: rectangular (weighted) matrix
model: character ('bernoulli', 'poisson', 'gaussian')
dimLabels: labels of each dimension (in row, in columns)
covarList: and optional list of covariates, each of whom must have the same dimension as incidenceMatrix
optimize()function to perform optimization
BipartiteSBM_fit$optimize(estimOptions = list())
estimOptions: a list of parameters controlling the inference algorithm and model selection. See details.
setModel()method to select a specific model among the ones fitted during the optimization. Fields of the current SBM_fit will be updated accordingly.
BipartiteSBM_fit$setModel(index)
index: integer, the index of the model to be selected (row number in storedModels)
reorder()permute group labels by order of decreasing probability
BipartiteSBM_fit$reorder()
show()show method
BipartiteSBM_fit$show(type = "Fit of a Bipartite Stochastic Block Model")
type: character used to specify the type of SBM
clone()The objects of this class are cloneable with this method.
BipartiteSBM_fit$clone(deep = FALSE)
deep: Whether to make a deep clone.