## 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

## 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