MultipartiteSBM_fit: R6 Class definition of a Multipartite SBM fit

Description Details Super classes Active bindings Methods

Description

R6 Class definition of a Multipartite SBM fit

R6 Class definition of a Multipartite SBM fit

Details

This class is designed to give a representation and adjust a Multipartite SBM fitted with GREMLIN.

The list of parameters estimOptions essentially tunes the optimization process and the variational EM algorithm, with the following parameters

Super classes

sbm::SBM -> sbm::MultipartiteSBM -> MultipartiteSBM_fit

Active bindings

loglik

double: approximation of the log-likelihood (variational lower bound) reached

ICL

double: value of the integrated classification log-likelihood

storedModels

data.frame of all models fitted (and stored) during the optimization

Methods

Public methods

Inherited methods

Method new()

constructor for Multipartite SBM

Usage
MultipartiteSBM_fit$new(netList)
Arguments
netList

list of SBM objects


Method optimize()

estimation of multipartiteSBM via GREMLINS

Usage
MultipartiteSBM_fit$optimize(estimOptions)
Arguments
estimOptions

options for MultipartiteBM


Method predict()

prediction under the currently estimated model

Usage
MultipartiteSBM_fit$predict()
Returns

a list of matrices matrix of expected values for each dyad


Method setModel()

method to select a specific model among the ones fitted during the optimization. Fields of the current MultipartiteSBM_fit will be updated accordingly.

Usage
MultipartiteSBM_fit$setModel(index)
Arguments
index

integer, the index of the model to be selected (row number in storedModels)


Method show()

show method

Usage
MultipartiteSBM_fit$show(type = "Fit of a Multipartite 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
MultipartiteSBM_fit$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.


GrossSBM/sbm documentation built on April 8, 2021, 5:53 a.m.