networkSampling

<p>this virtual class is the mother of all subtypes of networkSampling (either sampler or fit)
It is used to define a sampling model for a network.
It has a rSampling method which takes an adjacency matrix as an input and send back an object with class sampledNetwork.</p>

datasets

When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0
due to missing information between node pairs), it is possible to account for the underlying process
that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data
sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) <doi:10.1080/01621459.2018.1562934>.

Julien Chiquet

missSBM

Handling Missing Data in Stochastic Block Models

Pierre Barbillon

Timoth<c3><a9>e Tabouy

networkSampling function

<p>An object of class <code>R6ClassGenerator</code> of length 24.</p>

networkSampling: Definition of R6 Class 'networkSampling'

Description

Usage

Arguments

Format