| SimpleSBM_fit_MNAR | R Documentation |
It is not designed to be called directly by the user.
sbm::SBM -> sbm::SimpleSBM -> SimpleSBM_fit -> SimpleSBM_fit_noCov -> SimpleSBM_MNAR_noCov
vExpecdouble: variational approximation of the expectation complete log-likelihood
SimpleSBM_MNAR_noCov$new()constructor for simpleSBM_fit for missSBM purpose
SimpleSBM_MNAR_noCov$new(networkData, clusterInit)
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 with nbBlocks levels.
SimpleSBM_MNAR_noCov$update_parameters()update parameters estimation (M-step)
SimpleSBM_MNAR_noCov$update_parameters(nu = NULL)
nucurrently imputed values
SimpleSBM_MNAR_noCov$update_blocks()update variational estimation of blocks (VE-step)
SimpleSBM_MNAR_noCov$update_blocks(log_lambda = 0)
log_lambdaadditional term sampling dependent used to de-bias estimation of tau
SimpleSBM_MNAR_noCov$polish_log_tau()for each node, the complete-data log-likelihood it would contribute to
each class if hard-assigned there (theta/pi held fixed), used to decide node-swap
moves in missSBM_fit$polish(). Unlike update_blocks()'s tau update (which
combines the observed- and imputed-part E-steps as-is), this subtracts one copy of
log(pi): both E-step calls add it, so summing them double-counts it relative to
vExpec's convention – verified numerically to matter (see git history).
SimpleSBM_MNAR_noCov$polish_log_tau(log_lambda = 0)
log_lambdaadditional sampling-design-dependent term, added as-is
an N x Q matrix
SimpleSBM_MNAR_noCov$clone()The objects of this class are cloneable with this method.
SimpleSBM_MNAR_noCov$clone(deep = FALSE)
deepWhether to make a deep clone.
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