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Integration Network
It constructs a Consensus Network which identifies the general information of all the layers and Specific Networks for each layer with the information present only in that layer and not in all the others.The method is described in Policastro et al. (2024) "INet for network integration"
Clustering for networks
Facilitates network clustering and evaluation of cluster configurations.
Network Explorer
Social network analysis has become an essential tool in the study of complex systems. 'NetExplorer' allows to visualize and explore complex systems. It is based on 'd3js' library that brings 1) Graphical user interface; 2) Circular, linear, multilayer and force Layout; 3) Network live exploration and 4) SVG exportation.
ROBustness in Network
Assesses the robustness of the community structure of a network found by one or more community detection algorithm to give indications about their reliability. It detects if the community structure found by a set of algorithms is statistically significant and compares the different selected detection algorithms on the same network. robin helps to choose among different community detection algorithms the one that better fits the network of interest. Reference in Policastro V., Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) < https://journal.r-project.org/archive/2021/RJ-2021-040/index.html>.
Geographic Networks
Provides classes and methods for handling networks or graphs whose nodes are geographical (i.e. locations in the globe). The functionality includes the creation of objects of class geonetwork as a graph with node coordinates, the computation of network measures, the support of spatial operations (projection to different Coordinate Reference Systems, handling of bounding boxes, etc.) and the plotting of the geonetwork object combined with supplementary cartography for spatial representation.
Statistical Network Analysis of Animal Social Networks
Obtain network structures from animal GPS telemetry observations and statistically analyse them to assess their adequacy for social network analysis. Methods include pre-network data permutations, bootstrapping techniques to obtain confidence intervals for global and node-level network metrics, and correlation and regression analysis of the local network metrics.
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)
Parallel Mutual Information Estimation for Gene Network Reconstruction
Parallel estimation of the mutual information based on entropy
estimates from k-nearest neighbors distances and algorithms for the
reconstruction of gene regulatory networks
(Sales et al, 2011
Retrieve Network Statistics Including Available TCP Ports
R interface for the 'netstat' command line utility used to retrieve and parse commonly used network statistics, including available and in-use transmission control protocol (TCP) ports. Primers offering technical background information on the 'netstat' command line utility are available in the "Linux System Administrator's Manual" by Michael Kerrisk (2014) < https://man7.org/linux/man-pages/man8/netstat.8.html>, and on the Microsoft website (2017) < https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/netstat>.
Client for the Comprehensive Knowledge Archive Network ('CKAN') API
Client for 'CKAN' API (< https://ckan.org/>). Includes interface to 'CKAN' 'APIs' for search, list, show for packages, organizations, and resources. In addition, provides an interface to the 'datastore' API.