missSBM_collection function

An R6 class to represent a collection of SBM fits with missing data

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()

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)

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

• list("missSBM_collection$new()")

• list("missSBM_collection$estimate()")

• list("missSBM_collection$explore()")

• list("missSBM_collection$plot()")

• list("missSBM_collection$show()")

• list("missSBM_collection$print()")

• list("missSBM_collection$clone()")

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.