SimpleSBM_fit_noCov: This internal class is designed to adjust a binary Stochastic...

In jchiquet/missSBM: Handling Missing Data in Stochastic Block Models

This internal class is designed to adjust a binary Stochastic Block Model in the context of missSBM.

Description

This internal class is designed to adjust a binary Stochastic Block Model in the context of missSBM.

This internal class is designed to adjust a binary Stochastic Block Model in the context of missSBM.

Details

It is not designed not be call by the user

Super classes

sbm::SBM -> sbm::SimpleSBM -> missSBM::SimpleSBM_fit -> SimpleSBM_fit_noCov

Active bindings

imputation

the matrix of imputed values

vExpec

double: variational approximation of the expectation complete log-likelihood

vExpec_corrected

double: variational approximation of the expectation complete log-likelihood with correction to be comparable with MNAR criteria

Methods

Public methods

• SimpleSBM_fit_noCov$update_parameters()

• SimpleSBM_fit_noCov$update_blocks()

• SimpleSBM_fit_noCov$clone()

Inherited methods

• sbm::SBM$print()
• sbm::SBM$rNetwork()
• sbm::SimpleSBM$plot()
• sbm::SimpleSBM$predict()
• sbm::SimpleSBM$rEdges()
• sbm::SimpleSBM$rMemberships()
• sbm::SimpleSBM$show()
• missSBM::SimpleSBM_fit$doVEM()
• missSBM::SimpleSBM_fit$initialize()
• missSBM::SimpleSBM_fit$reorder()

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Method update_parameters()

update parameters estimation (M-step)

Usage

SimpleSBM_fit_noCov$update_parameters(...)

Arguments

...

additional arguments, only required for MNAR cases

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Method update_blocks()

update variational estimation of blocks (VE-step)

Usage

SimpleSBM_fit_noCov$update_blocks(...)

Arguments

...

additional arguments, only required for MNAR cases

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Method clone()

The objects of this class are cloneable with this method.

Usage

SimpleSBM_fit_noCov$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

jchiquet/missSBM documentation built on Oct. 25, 2023, 5:30 a.m.