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Model Estimation

Main estimation functions and controls for fitting joint models of networks and attributes.

iglm()
Construct an iglm Model Specification Object
control.iglm()
Set Control Parameters for iglm Estimation
iglm.object.generator
iglm Objects (R6 Class)

Data Preparation & Setup

Functions and R6 classes to manage network and attribute data.

iglm.data()
Constructor for the iglm.data R6 object
iglm.data_generator
Networks with Unit-Level Attributes (R6 Class)

Model Simulation

Functions to simulate network and attribute outcomes from fitted models.

simulate_iglm()
Simulate Responses and Connections

MCMC Samplers

Sampler configurations and classes for network and attribute variables.

sampler.iglm()
Constructor for a iglm Sampler
sampler.iglm.generator
iglm Sampler Settings (R6 Class)
sampler.net.attr()
Constructor for Single Component Sampler Settings
sampler.net.attr.generator
Single Component Sampler Settings (R6 Class)

Diagnostics & Results

Classes and functions for retrieving results, statistics, and assessment.

results()
Constructor for the results R6 Object
results.generator
iglm Estimation and Simulation Results (R6 Class)
statistics()
Compute Statistics

Model Specification & Custom Terms

Utilities for defining custom terms and analyzing sufficient statistics.

Datasets

Example network and attribute datasets included in the package.

copenhagen
Copenhagen Network Study
state_twitter
Twitter (X) data list for U.S. state legislators (10-state subset)