SimpleSBM_fit_MNAR {missSBM}R Documentation

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 -> missSBM::SimpleSBM_fit_noCov -> SimpleSBM_MNAR_noCov

Active bindings

imputation

the matrix of imputed values

vExpec

double: variational approximation of the expectation complete log-likelihood

Methods

Public methods

Inherited methods

Method new()

constructor for simpleSBM_fit for missSBM purpose

Usage
SimpleSBM_fit_MNAR$new(networkData, clusterInit)
Arguments
networkData

a structure to store network under missing data condition: either a matrix possibly with NA, or a missSBM:::partlyObservedNetwork

clusterInit

Initial clustering: a vector with size ncol(adjacencyMatrix), providing a user-defined clustering with nbBlocks levels.


Method update_parameters()

update parameters estimation (M-step)

Usage
SimpleSBM_fit_MNAR$update_parameters(nu = NULL)
Arguments
nu

currently imputed values


Method update_blocks()

update variational estimation of blocks (VE-step)

Usage
SimpleSBM_fit_MNAR$update_blocks(log_lambda = 0)
Arguments
log_lambda

additional term sampling dependent used to de-bias estimation of tau


Method clone()

The objects of this class are cloneable with this method.

Usage
SimpleSBM_fit_MNAR$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.


[Package missSBM version 1.0.4 Index]