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iglm (version 1.1)

Regression under Network Interference

Description

An implementation of generalized linear models (GLMs) for studying relationships among attributes in connected populations, where responses of connected units can be dependent, as introduced by Fritz et al. (2025) . 'igml' extends GLMs for independent responses to dependent responses and can be used for studying spillover in connected populations and other network-mediated phenomena.

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Version

Install

install.packages('iglm')

Monthly Downloads

147

Version

1.1

License

GPL-3

Maintainer

Cornelius Fritz

Last Published

November 28th, 2025

Functions in iglm (1.1)

control.iglm

Set Control Parameters for iglm Estimation
model.terms

Model specification for a `iglm' object
count_statistics

Compute Statistics
results.generator

R6 Class for Storing iglm Estimation and Simulation Results
create_userterms_skeleton

Generate the Skeleton for an R package to implement additional iglm terms
iglm.data_generator

A R6 class to represent networks with unit-level attributes
results

Constructor for the results R6 Object
iglm.data

Constructor for the iglm.data R6 object
iglm

Construct a iglm Model Specification Object
iglm.object.generator

An R6 class for Network GLM (Generalized Linear Model) Objects
sampler.net.attr

Constructor for Single Component Sampler Settings
sampler.iglm.generator

R6 Class for iglm Sampler Settings
rice

A network of friendships between students at Rice University.
simulate_iglm

Simulate responses and connections
sampler.net.attr.generator

R6 Class for Single Component Sampler Settings
sampler.iglm

Constructor for a iglm Sampler
state_twitter

Twitter (X) data list for U.S. state legislators (10-state subset)