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Top-level fitting functions

Main functions for estimating and sampling from an SBM with missing data

estimateMissSBM()
Estimation of simple SBMs with missing data
observeNetwork()
Observe a network partially according to a given sampling design
missSBM_param()
Control of a missSBM fit

Main classes of objects

Description of objects missSBM_fit and missSBM_collection. The class missSBM_fit is the more central class of object, embedding fits for both the SBM and the sampling model. The class missSBM_collection defines objects for storing a collection of missSBM_fit, resulting from the the top-level function estimateMissSBM().

missSBM_fit
An R6 class to represent an SBM fit with missing data
coef(<missSBM_fit>)
Extract model coefficients
fitted(<missSBM_fit>)
Extract model fitted values from object missSBM_fit, return by estimateMissSBM()
predict(<missSBM_fit>)
Prediction of a missSBM_fit (i.e. network with imputed missing dyads)
plot(<missSBM_fit>)
Visualization for an object missSBM_fit
missSBM_collection
An R6 class to represent a collection of SBM fits with missing data

Data sets

war
War data set
frenchblog2007
Political Blogosphere network prior to 2007 French presidential election
er_network
ER ego centered network