measure.dynamics {igraph} | R Documentation |
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.
measure.dynamics.idage (graph, agebins = 300, iterations = 5, error=TRUE, time.window = NULL, number = FALSE, cites=FALSE, norm.method="old") measure.dynamics.id(graph, iterations = 5, error=TRUE, time.window = NULL, number = FALSE, cites=FALSE, norm.method="old", debug=FALSE, debugdeg=0, which=2) measure.dynamics.d.d(graph, vtime, etime, iterations = 5) measure.dynamics.citedcat.id.age(graph, categories, agebins = 300, iterations = 5, norm = c(1, 1, 1)) measure.dynamics.citingcat.id.age(graph, categories, agebins = 300, iterations = 5, norm = c(1, 1, 1)) measure.dynamics.lastcit(graph, agebins, iterations=5, norm.method="old", number=FALSE) measure.dynamics.age(graph, agebins, iterations=5, norm.method="old", number=FALSE) measure.dynamics.citedcat(graph, categories, iterations=5, number=FALSE, norm.method="old") measure.dynamics.citingcat.citedcat(graph, categories, iterations=5, number=FALSE, norm.method="old", norm=c(1,1))
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. |
time.window |
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vtime |
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etime |
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categories |
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norm |
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number |
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norm.method |
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error |
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cites |
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debug |
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debugdeg |
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which |
The functions should be considered as experimental, so no detailed documentation yet. Sorry.
TODO
Gabor Csardi csardi@rmki.kfki.hu