MultiplexSBM_fit: R6 Class definition of a Multiplex SBM fit

Description Details Super classes Active bindings Methods

Description

R6 Class definition of a Multiplex SBM fit

R6 Class definition of a Multiplex SBM fit

Details

This class is designed to give a representation and adjust a Multiplex 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 -> sbm::MultipartiteSBM_fit -> MultiplexSBM_fit

Active bindings

nbBlocks

vector of size 2: number of blocks (rows, columns)

dependentNetwork

: connection parameters in each network

storedModels

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

namesLayers

: names of the various Networks

Methods

Public methods

Inherited methods

Method new()

constructor for Multiplex SBM

Usage
MultiplexSBM_fit$new(netList, dependentNet = FALSE)
Arguments
netList

list of SBM object with

dependentNet

boolean indicating whether dependence is assumed between networks beyond the common dependence on the latent variables


Method optimize()

estimation of multipartiteSBM via GREMLINS

Usage
MultiplexSBM_fit$optimize(estimOptions)
Arguments
estimOptions

options for MultipartiteBM


Method plot()

plot Multiplex Network

Usage
MultiplexSBM_fit$plot(
  type = c("data", "expected"),
  ordered = TRUE,
  plotOptions = list()
)
Arguments
type

character for the type of plot: either 'data' (true connection), 'expected' (fitted connection). Default to 'data'.

ordered

TRUE is the matrices are plotted after reorganization with the blocks. Default value = TRUE

plotOptions

list of plot options for the matrix view


Method show()

show method

Usage
MultiplexSBM_fit$show(type = "Fit of a Multiplex Stochastic Block Model")
Arguments
type

character used to specify the type of SBM


Method predict()

prediction under the currently estimated model

Usage
MultiplexSBM_fit$predict()
Returns

a list of matrices matrix of expected values for each dyad


Method clone()

The objects of this class are cloneable with this method.

Usage
MultiplexSBM_fit$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.


GrossSBM/sbm documentation built on Oct. 8, 2021, 6:23 p.m.