Found 1049 packages in 0.04 seconds
Analyzing Partial Rankings in Networks
Implements methods for centrality related analyses of networks.
While the package includes the possibility to build more than 20 indices,
its main focus lies on index-free assessment of centrality via partial
rankings obtained by neighborhood-inclusion or positional dominance. These
partial rankings can be analyzed with different methods, including
probabilistic methods like computing expected node ranks and relative
rank probabilities (how likely is it that a node is more central than another?).
The methodology is described in depth in the vignettes and in
Schoch (2018)
Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models
An integrated set of extensions to the 'ergm' package to analyze and simulate network evolution based on exponential-family random graph models (ERGM). 'tergm' is a part of the 'statnet' suite of packages for network analysis. See Krivitsky and Handcock (2014)
Tools for Temporal Social Network Analysis
Temporal SNA tools for continuous- and discrete-time longitudinal networks having vertex, edge, and attribute dynamics stored in the 'networkDynamic' format. This work was supported by grant R01HD68395 from the National Institute of Health.
Bayesian Network Structure Learning from Data with Missing Values
Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.
Transmissions and Receptions in an End to End Network
Computes the expectation of the number of transmissions and receptions considering an End-to-End transport model with limited number of retransmissions per packet. It provides theoretical results and also estimated values based on Monte Carlo simulations. It is also possible to consider random data and ACK probabilities.
Transmissions and Receptions in a Hop by Hop Network
Computes the expectation of the number of transmissions and receptions considering a Hop-by-Hop transport model with limited number of retransmissions per packet. It provides the theoretical results shown in Palma et. al.(2016)
Network Analysis on the Norwegian Road Network
A collection of GIS (Geographic Information System) functions in R, created for use in Statistics Norway. The functions are primarily related to network analysis on the Norwegian road network.
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.
Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges
A set of extensions for the 'ergm' package to fit weighted networks whose edge weights are counts. See Krivitsky (2012)
Geometrical Functionality of the 'spatstat' Family
Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)