Time-Ordered and Time-Aggregated Network Analyses
Applies a function (typically a descriptive statistic) to multiple tim...
Generates vector-clock latencies for each individual at each time.
Generates multiple time-aggregated networks from a time-ordered networ...
Constructs a weighted time-aggregated network from a time-ordered netw...
Constructs matrix of sequential time windows suitable for slicing time...
Constructs matrix of increasingly large time windows suitable for asse...
Generates a time-ordered network from an interaction list.
Generates a time-ordered network from a data frame listing all directe...
Generates a data frame listing all directed edges in a time-ordered ne...
Determines the maximum value of each row of a matrix; used as a conven...
Determines the mean value of each row of a matrix; used as a convenien...
Plots a time-aggregated network
Plots a time-aggregated network.
Plots a time-ordered network.
Does all the work for edge_randomization and randomized_edges. An ...
Resamples data based on vertex identity.
Resamples data based on event time.
Randomize temporal networks
Simulates the effect of insufficient sampling by data rarefaction.
Determines a path (shortest by the least number of unique vertices) be...
Determines a path (shortest by the least time) between a vertex at a s...
Simulates the perfect spread of a resource on a time-ordered network.
Swaps two elements in a data frame. An internal function.
A helper function to assess differences in spreading potential by vert...
Approaches for incorporating time into network analysis. Methods include: construction of time-ordered networks (temporal graphs); shortest-time and shortest-path-length analyses; resource spread calculations; data resampling and rarefaction for null model construction; reduction to time-aggregated networks with variable window sizes; application of common descriptive statistics to these networks; vector clock latencies; and plotting functionalities. The package supports <doi:10.1371/journal.pone.0020298>.