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, start.vertex = 0, agebins = 300, iterations = 5, significance = 0, estind = NULL, estage = NULL, number = FALSE, time.window = NULL) measure.dynamics.id(graph, start.vertex = 0, iterations = 5, significance = 0, estind = NULL, estage = NULL, number = FALSE, time.window = NULL) measure.dynamics.d.d(graph, vtime, etime, iterations = 5, sd = TRUE, no = FALSE) measure.dynamics.citedcat.id.age(graph, categories, agebins = 300, iterations = 5, significance = 0, number = FALSE, norm = c(1, 1, 1)) measure.dynamics.citingcat.id.age(graph, categories, agebins = 300, iterations = 5, significance = 0, number = FALSE, norm = c(1, 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. |
start.vertex |
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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. |
significance |
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estind |
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estage |
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number |
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time.window |
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vtime |
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etime |
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sd |
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no |
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categories |
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norm |
The functions should be considered as experimental, so no detailed documentation yet. Sorry.
TODO
Gabor Csardi csardi@rmki.kfki.hu