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Links tostocnet

RSiena - Siena - Simulation Investigation for Empirical Network Analysis

The main purpose of this package is to perform simulation-based estimation of stochastic actor-oriented models for longitudinal network data collected as panel data. Dependent variables can be single or multivariate networks, which can be directed, non-directed, or two-mode; and associated actor variables. There are also functions for testing parameters and checking goodness of fit. An overview of these models is given in Snijders (2017), <doi:10.1146/annurev-statistics-060116-054035>.

Last updated

longitudinal-datarsienasocial-network-analysisstatistical-network-analysisstatisticscpp

10.36 score 116 stars 1 dependents 497 scripts 1.7k downloads

goldfish - Statistical Network Models for Dynamic Network Data

Tools for fitting statistical network models to dynamic network data. Can be used for fitting both dynamic network actor models ('DyNAMs') and relational event models ('REMs'). Stadtfeld, Hollway, and Block (2017a) <doi:10.1177/0081175017709295>, Stadtfeld, Hollway, and Block (2017b) <doi:10.1177/0081175017733457>, Stadtfeld and Block (2017) <doi:10.15195/v4.a14>, Hoffman et al. (2020) <doi:10.1017/nws.2020.3>.

Last updated

dynamnetwork-modellingremstatistical-network-analysiscpp

7.68 score 66 stars 61 scripts 251 downloads

manynet - Many Ways to Make, Modify, Mark, and Measure Myriad Networks

Many tools for making, modifying, 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, on directed, multiplex, multimodal, signed, and other networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing networks with sensible defaults.

Last updated

diffusion-modelsgraphsnetwork-analysis

7.32 score 13 stars 3 dependents 50 scripts 855 downloads

migraph - Inferential Methods for Multimodal and Other Networks

A set of tools for testing networks. It includes functions for univariate and multivariate conditional uniform graph and quadratic assignment procedure testing, and network regression. The package is a complement to 'Multimodal Political Networks' (2021, ISBN:9781108985000), and includes various datasets used in the book. Built on the 'manynet' package, all functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode and two-mode (bipartite) networks.

Last updated

igraphmultilevel-networksmultimodal-networknetwork-analysissna

6.90 score 41 stars 48 scripts 977 downloads

autograph - Automatic Plotting and Theming of Many Graphs

Visual exploration and presentation of networks should not be difficult. This package includes functions for plotting networks and network-related metrics with sensible and pretty defaults. It includes 'ggplot2'-based plot methods for many popular network package classes. It also includes some novel layout algorithms, and options for straightforward, consistent themes.

Last updated

graphsnetworkplotting

4.72 score 2 stars 1 dependents 16 scripts 803 downloads

ERPM - Exponential Random Partition Models

Simulates and estimates the Exponential Random Partition Model presented in the paper Hoffman, Block, and Snijders (2023) <doi:10.1177/00811750221145166>. It can also be used to estimate longitudinal partitions, following the model proposed in Hoffman and Chabot (2023) <doi:10.1016/j.socnet.2023.04.002>. The model is an exponential family distribution on the space of partitions (sets of non-overlapping groups) and is called in reference to the Exponential Random Graph Models (ERGM) for networks.

Last updated

4.04 score 11 stars 195 downloads

netrics - Many Ways to Measure and Classify Membership for Networks, Nodes, and Ties

Many tools for calculating network, node, or tie marks, measures, motifs and memberships of many different types of networks. Marks identify structural positions, measures quantify network properties, memberships classify nodes into groups, and motifs tabulate substructure participation. All functions operate with all classes of network data covered in 'manynet', and on directed, undirected, multiplex, multimodal, signed, and other networks.

Last updated

centralitycommunity-detectionnetwork-analysisresiliencetopology

4.02 score 1 dependents 3 scripts 640 downloads