- netdiffuseR: Analysis of Diffusion and Contagion Processes on Networks
- fakeDynEdgelist: Fake dynamic edgelist
Fake dynamic edgelist
A data frame used for examples in reading edgelist format networks. This
edgelist can be merged with the dataset
A data frame with 22 rows and 4 variables
Strength of the tie
Integer with the time of the spell
George G. Vega Yon
Generated for the package
Other diffusion datasets:
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- as.array.diffnet: Coerce a diffnet graph into an array
- as_diffnet: Creates a 'diffnet' class object
- brfarmers: Brazilian Farmers
- brfarmersDiffNet: 'diffnet' version of the Brazilian Farmers data
- c.diffnet: Combine diffnet objects
- classify_adopters: Classify adopters accordingly to Time of Adoption and...
- classify_graph: Analyze an R object to identify the class of graph (if any)
- cumulative_adopt_count: Cummulative count of adopters
- dgr: Indegree, outdegree and degree of the vertices
- diag_expand: Creates a square matrix suitable for spatial statistics...
- diffnet-arithmetic: 'diffnet' Arithmetic and Logical Operators
- diffnet_check_attr_class: Infer whether 'value' is dynamic or static.
- diffnet_index: Indexing diffnet objects (on development)
- diffnetmatmult: Matrix multiplication
- diffnet_to_igraph: Convertion between graph classes
- diffusion-data: Diffusion Network Datasets
- diffusionMap: Creates a heatmap based on a graph layout and a vertex...
- drawColorKey: Draw a color key in the current device
- edgelist_to_adjmat: Conversion between adjacency matrix and edgelist
- edges_coords: Compute ego/alter edge coordinates considering alter's size...
- egonet_attrs: Retrieve alter's attributes (network effects)
- ego_variance: Computes variance of Y at ego level
- exposure: Ego exposure
- fakeDynEdgelist: Fake dynamic edgelist
- fakeEdgelist: Fake static edgelist
- fakesurvey: Fake survey data
- fakesurveyDyn: Fake longitudinal survey data
- grid_distribution: Distribution over a grid
- hazard_rate: Network Hazard Rate
- infection: Susceptibility and Infection
- isolated: Find and remove isolated vertices
- kfamily: Korean Family Planning
- kfamilyDiffNet: 'diffnet' version of the Korean Family Planning data
- medInnovations: Medical Innovation
- medInnovationsDiffNet: 'diffnet' version of the Medical Innovation data
- moran: Computes Moran's I correlation index
- netdiffuseR: netdiffuseR
- netdiffuseR-graphs: Network data formats
- netdiffuseR-options: 'netdiffuseR' default options
- nvertices: Count the number of vertices/edges/slices in a graph
- permute_graph: Permute the values of a matrix
- plot_adopters: Visualize adopters and cumulative adopters
- plot_diffnet: Plot the diffusion process
- plot_diffnet2: Another way of visualizing diffusion
- plot_infectsuscep: Plot distribution of infect/suscep
- plot_threshold: Threshold levels through time
- pretty_within: Pretty numbers within a range.
- rdiffnet: Random diffnet network
- read_pajek: Read foreign graph formats
- read_ucinet_head: Reads UCINET files
- recode: Recodes an edgelist such that ids go from 1 to n
- rescale_vertex_igraph: Rescale vertex size to be used in 'plot.igraph'.
- rewire_graph: Graph rewiring algorithms
- rgraph_ba: Scale-free and Homophilic Random Networks
- rgraph_er: Erdos-Renyi model
- rgraph_ws: Watts-Strogatz model
- ring_lattice: Ring lattice graph
- round_to_seq: Takes a numeric vector and maps it into a finite length...
- select_egoalter: Calculate the number of adoption changes between ego and...
- struct_equiv: Structural Equivalence
- struct_test: Structure dependence test
- survey_to_diffnet: Convert survey-like data and edgelists to a 'diffnet' object
- threshold: Retrive threshold levels from the exposure matrix
- toa_diff: Difference in Time of Adoption (TOA) between individuals
- toa_mat: Time of adoption matrix
- transformGraphBy: Apply a function to a graph considering non-diagonal...
- vertex_covariate_compare: Comparisons at dyadic level
- vertex_covariate_dist: Computes covariate distance between connected vertices
- weighted_var: Computes weighted variance