SimpleSBM_fit_MNAR function

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.

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

• list("SimpleSBM_fit_MNAR$new()")

• list("SimpleSBM_fit_MNAR$update_parameters()")

• list("SimpleSBM_fit_MNAR$update_blocks()")

• list("SimpleSBM_fit_MNAR$clone()")

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.