missSBM_collection {missSBM} | R Documentation |
An R6 class to represent a collection of SBM fits with missing data
Description
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()
Active bindings
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
Methods
Public methods
Method new()
constructor for networkSampling
Usage
missSBM_collection$new(partlyObservedNet, sampling, clusterInit, control)
Arguments
partlyObservedNet
An object with class
partlyObservedNetwork
.sampling
The sampling design for the modelling of missing data: MAR designs ("dyad", "node") and MNAR designs ("double-standard", "block-dyad", "block-node" ,"degree")
clusterInit
Initial clustering: a list of vectors, each with size
ncol(adjacencyMatrix)
.control
a list of parameters controlling advanced features. Only 'trace' and 'useCov' are relevant here. See
estimateMissSBM()
for details.
Method estimate()
method to launch the estimation of the collection of models
Usage
missSBM_collection$estimate(control)
Arguments
control
a list of parameters controlling the variational EM algorithm. See details of function
estimateMissSBM()
Method explore()
method for performing exploration of the ICL
Usage
missSBM_collection$explore(control)
Arguments
control
a list of parameters controlling the exploration, similar to those found in the regular function
estimateMissSBM()
Method plot()
plot method for missSBM_collection
Usage
missSBM_collection$plot(type = c("icl", "elbo", "monitoring"))
Arguments
type
the type specifies the field to plot, either "icl", "elbo" or "monitoring". Default is "icl"
Method show()
show method for missSBM_collection
Usage
missSBM_collection$show()
Method print()
User friendly print method
Usage
missSBM_collection$print()
Method clone()
The objects of this class are cloneable with this method.
Usage
missSBM_collection$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
## 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)