Showing 4 of total 4 results (show query)
igraph
igraph:Network Analysis and Visualization
Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
Maintained by Kirill Müller. Last updated 10 hours ago.
complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp
584 stars 21.14 score 31k scripts 1.9k dependents
stocnet
manynet:Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
Many tools for making, modifying, mapping, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode, two-mode (bipartite), and sometimes three-mode networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing and visualizing networks with sensible defaults.
Maintained by James Hollway. Last updated 3 months ago.
diffusion-modelsgraphsnetwork-analysis
13 stars 6.41 score 35 scripts 1 dependents
muriteams
ergmito:Exponential Random Graph Models for Small Networks
Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics as shown in Vega Yon et al. (2020) <DOI:10.1016/j.socnet.2020.07.005>. As a difference from the 'ergm' package, 'ergmito' circumvents using Markov-Chain Maximum Likelihood Estimator (MC-MLE) and instead uses Maximum Likelihood Estimator (MLE) to fit ERGMs for small networks. As exhaustive enumeration is computationally feasible for small networks, this R package takes advantage of this and provides tools for calculating likelihood functions, and other relevant functions, directly, meaning that in many cases both estimation and simulation of ERGMs for small networks can be faster and more accurate than simulation-based algorithms.
Maintained by George Vega Yon. Last updated 2 years ago.
ergmexponential-random-graph-modelsstatisticsopenblascppopenmp
9 stars 5.49 score 34 scripts
hwarden162
rhype:Work with Hypergraphs in R
Create and manipulate hypergraph objects. This early version of rhype allows for the output of matrices associated with the hypergraphs themselves. It also uses these matrices to calculate hypergraph spectra and perform spectral comparison. Functionality coming soon includes calculation of hyperpaths and hypergraph centrality measures.
Maintained by Hugh Warden. Last updated 3 years ago.
3 stars 4.18 score 5 scripts