A collection of dynamic network data sets from various sources and multiple authors represented as 'networkDynamic'-formatted objects.

Simulates the extinction of species in ecological networks and it analyzes
             its cascading effects, described in Dunne et al. (2002) <doi:10.1073/pnas.192407699>.

A network Maze generator that creates different types of network mazes.

This is an R implementation of the netinf algorithm (Gomez Rodriguez, Leskovec, and Krause, 2010)<doi:10.1145/1835804.1835933>. Given a set of events that spread between a set of nodes the algorithm infers the most likely stable diffusion network that is underlying the diffusion process.

An implementation of some of the core 'network' package functionality based on a 
    simplified data structure that is faster in many research applications. This package is designed 
    for back-end use in the 'statnet' family of packages, including 'EpiModel'. Support is provided for
    binary and weighted, directed and undirected, bipartite and unipartite networks; no current 
    support for multigraphs, hypergraphs, or loops.

Collection of functions for fast manipulation, handling, and analysis of large-scale
    networks based on family and social data. Functions are utility functions used to manipulate data
    in three "formats": sparse adjacency matrices, pedigree trio family data, and pedigree family data.
    When possible, the functions should be able to handle millions of data points quickly for use in combination
    with data from large public national registers and databases.
    Kenneth Lange (2003, ISBN:978-8181281135).

Linear regression model with nonparametric network effects on network-linked observations. The model is proposed by Le and Li (2022) <arXiv:2007.00803> and is assumed on observations that are connected by a network or similar relational data structure. The model does not assume that the relational data or network structure to be precisely observed; thus, the method is provably robust to a certain level of perturbation of the network structure. The package contains the estimation and inference function for the model.