MultiplexSBM_fit: R6 Class definition of a Multiplex SBM fit

In GrossSBM/sbm: Stochastic Blockmodels

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

• "nbCores"integer for number of cores used. Default is 2

• "verbosity"integer for verbosity (0, 1). Default is 1

• "nbBlocksRange"List of length the number of functional groups, each element supplying the minimal and maximal number of blocks to be explored. The names of the list must be the names of the functional groups. Default value is from 1 to 10)

• "initBM"Boolean. True if using simple and bipartite SBM as initialisations. Default value = TRUE

• "maxiterVEM"Number of max. number of iterations in the VEM. Default value = 100

• "maxiterVE"Number of max. number of iterations in the VE. Default value = 100

Super classes

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

Active bindings

dependentNetwork

: connection parameters in each network

Methods

Public methods

• MultiplexSBM_fit$new()

• MultiplexSBM_fit$optimize()

• MultiplexSBM_fit$clone()

Inherited methods

• sbm::SBM$rNetwork()

• sbm::MultipartiteSBM$plot()

• sbm::MultipartiteSBM$print()

• sbm::MultipartiteSBM_fit$predict()

• sbm::MultipartiteSBM_fit$setModel()

• sbm::MultipartiteSBM_fit$show()

---

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 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 April 8, 2021, 5:53 a.m.