| 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
imputationthe matrix of imputed values
vExpecdouble: 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$new(networkData, clusterInit)
Arguments
networkDataa structure to store network under missing data condition: either a matrix possibly with NA, or a missSBM:::partlyObservedNetwork
clusterInitInitial clustering: a vector with size
ncol(adjacencyMatrix), providing a user-defined clustering withnbBlockslevels.
Method update_parameters()
update parameters estimation (M-step)
Usage
SimpleSBM_fit_MNAR$update_parameters(nu = NULL)
Arguments
nucurrently imputed values
Method update_blocks()
update variational estimation of blocks (VE-step)
Usage
SimpleSBM_fit_MNAR$update_blocks(log_lambda = 0)
Arguments
log_lambdaadditional term sampling dependent used to de-bias estimation of tau
Method clone()
The objects of this class are cloneable with this method.
Usage
SimpleSBM_fit_MNAR$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.