measure.dynamics

0th

Percentile

Measuring the driving force in evolving networks

These functions assume a simple evolving network model and measure the functional form of a so-called attractiveness function governing the evolution of the network.

Keywords
graphs
Usage
measure.dynamics.idage(graph, agebins=300, iterations=5, sd=FALSE,
                       estind=NULL, estage=NULL)
Arguments
graph
The graph of which the evolution is quantified. It is assumed that the vertices were added in increasing order of vertex id.
agebins
Numeric constant, the number of bins to use for measuring aging.
iterations
Numeric constant, number of iterations to perform while calculating the attractiveness and the total attractiveness function.
sd
Logical, should an estimation of the error also calculated.
estind
estage
Details

The functions should be considered as experimental, so no detailed documentation yet. Sorry.

Value

  • A named list with components akl (the attractiveness function), st (total attractiveness versus time), sd (only if the sd arguments was TRUE, the estimation of the error for the akl values).

Aliases
  • measure.dynamics
  • measure.dynamics.idage
Examples
g <- barabasi.game(10000)
mes <- measure.dynamics.idage(g, 20, sd=TRUE)
Documentation reproduced from package igraph, version 0.1.2, License: GPL version 2 or later (June, 1991)

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