missSBM_collection | R Documentation |
The function estimateMissSBM()
fits a collection of SBM with missing data for
a varying number of block. These models with class missSBM_fit
are stored in an instance
of an object with class missSBM_collection
, described here.
Fields are accessed via active binding and cannot be changed by the user.
This class comes with a set of R6 methods, some of them being useful for the user and exported
as S3 methods. See the documentation for show()
and print()
models
a list of models
ICL
the vector of Integrated Classification Criterion (ICL) associated to the models in the collection (the smaller, the better)
bestModel
the best model according to the ICL
vBlocks
a vector with the number of blocks
optimizationStatus
a data.frame summarizing the optimization process for all models
new()
constructor for networkSampling
missSBM_collection$new(partlyObservedNet, sampling, clusterInit, control)
partlyObservedNet
An object with class partlyObservedNetwork
.
sampling
The sampling design for the modelling of missing data: MAR designs ("dyad", "node") and MNAR designs ("double-standard", "block-dyad", "block-node" ,"degree")
clusterInit
Initial clustering: a list of vectors, each with size ncol(adjacencyMatrix)
.
control
a list of parameters controlling advanced features. Only 'trace' and 'useCov' are relevant here. See estimateMissSBM()
for details.
estimate()
method to launch the estimation of the collection of models
missSBM_collection$estimate(control)
control
a list of parameters controlling the variational EM algorithm. See details of function estimateMissSBM()
explore()
method for performing exploration of the ICL
missSBM_collection$explore(control)
control
a list of parameters controlling the exploration, similar to those found in the regular function estimateMissSBM()
plot()
plot method for missSBM_collection
missSBM_collection$plot(type = c("icl", "elbo", "monitoring"))
type
the type specifies the field to plot, either "icl", "elbo" or "monitoring". Default is "icl"
show()
show method for missSBM_collection
missSBM_collection$show()
print()
User friendly print method
missSBM_collection$print()
clone()
The objects of this class are cloneable with this method.
missSBM_collection$clone(deep = FALSE)
deep
Whether to make a deep clone.
## Uncomment to set parallel computing with future
## future::plan("multicore", workers = 2)
## Sample 75% of dyads in French political Blogosphere's network data
adjacencyMatrix <- missSBM::frenchblog2007 %>%
igraph::delete.vertices(1:100) %>%
igraph::as_adj () %>%
missSBM::observeNetwork(sampling = "dyad", parameters = 0.75)
collection <- estimateMissSBM(adjacencyMatrix, 1:5, sampling = "dyad")
class(collection)
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