Tools for Identifying Important Nodes in Networks

Includes assorted tools for network analysis. Bridge centrality; goldbricker; MDS, PCA, & eigenmodel network plotting.

Construction, Simulation and Analysis of Boolean Networks

Functions to reconstruct, generate, and simulate synchronous, asynchronous, probabilistic, and temporal Boolean networks. Provides also functions to analyze and visualize attractors in Boolean networks .

Fault Tolerant Simple Network of Workstations

Extension of the snow package supporting fault tolerant and reproducible applications, as well as supporting easy-to-use parallel programming - only one function is needed. Dynamic cluster size is also available.

Phylogenetic Reconstruction and Analysis

Allows for estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation (Schliep 2011). Offers methods for tree comparison, model selection and visualization of phylogenetic networks as described in Schliep et al. (2017).

Spatial Modeling on Stream Networks

Spatial statistical modeling and prediction for data on stream networks, including models based on in-stream distance (Ver Hoef, J.M. and Peterson, E.E., (2010) .) Models are created using moving average constructions. Spatial linear models, including explanatory variables, can be fit with (restricted) maximum likelihood. Mapping and other graphical functions are included.

Bootstrap Methods for Various Network Estimation Routines

Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices . Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for various estimation routines.

Interactive 3D Scatter Plots, Networks and Globes

Create interactive 3D scatter plots, network plots, and globes using the 'three.js' visualization library (< https://threejs.org>).

Software Tools for the Statistical Analysis of Network Data

Statnet is a collection of packages for statistical network analysis that are designed to work together because they share common data representations and 'API' design. They provide an integrated set of tools for the representation, visualization, analysis, and simulation of many different forms of network data. This package is designed to make it easy to install and load the key 'statnet' packages in a single step. Learn more about 'statnet' at < http://www.statnet.org>. Tutorials for many packages can be found at < https://github.com/statnet/Workshops/wiki>. For an introduction to functions in this package, type help(package='statnet').

Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation

Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) .

Generalized Multipartite Networks

We define generalized multipartite networks as the joint observation of several networks implying some common pre-specified groups of individuals. The aim is to fit an adapted version of the popular stochastic block model to multipartite networks, as described in Bar-hen, Barbillon and Donnet (2020) .