MultipartiteSBM_fit: R6 Class definition of a Multipartite SBM fit

In sbm: Stochastic Blockmodels

R6 Class definition of a Multipartite SBM fit

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

• "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 -> 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

• MultipartiteSBM_fit$new()

• MultipartiteSBM_fit$optimize()

• MultipartiteSBM_fit$predict()

• MultipartiteSBM_fit$setModel()

• MultipartiteSBM_fit$show()

• MultipartiteSBM_fit$clone()

Inherited methods

• sbm::SBM$rNetwork()
• sbm::MultipartiteSBM$plot()
• sbm::MultipartiteSBM$print()

---

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.

sbm documentation built on Jan. 9, 2023, 5:12 p.m.