igraph (version 0.4.1)

revolver: Measuring the driving force in evolving networks

Description

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.

Usage

evolver.d (nodes, kernel, outseq = NULL, outdist = NULL, m = 1, 
           directed = TRUE, verbose = igraph.par("verbose"))
revolver.d (graph, niter=5, sd=FALSE, norm=FALSE,
           cites=FALSE, expected=FALSE, error=TRUE, debug=numeric(),
           verbose=igraph.par("verbose"))
revolver.ad (graph, niter=5, agebins=max(vcount(graph)/7100, 10),
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE, error=TRUE,
            debug=matrix(nc=2, nr=0), verbose=igraph.par("verbose"))
revolver.ade (graph, cats, niter=5, agebins=max(vcount(graph)/7100, 10),
             sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
             error=TRUE, debug=matrix(nc=2, nr=0),
                        verbose=igraph.par("verbose"))
revolver.e (graph, cats, niter=5,
           sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
           error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.de (graph, cats, niter=5,
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.l (graph, niter=5, agebins=max(vcount(graph)/7100, 10),
           sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
           error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.dl (graph, niter=5, agebins=max(vcount(graph)/7100, 10),
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.el (graph, cats, niter=5, agebins=max(vcount(graph)/7100, 10),
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.r (graph, window, niter=5, sd=FALSE, norm=FALSE,
           cites=FALSE, expected=FALSE, error=TRUE, debug=numeric(),
           verbose=igraph.par("verbose"))
revolver.ar (graph, window, niter=5, agebins=max(vcount(graph)/7100, 10),
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE, error=TRUE,
            debug=matrix(nc=2, nr=0), verbose=igraph.par("verbose"))
revolver.di (graph, cats, niter=5,
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.adi (graph, cats, niter=5, agebins=max(vcount(graph)/7100, 10),
             sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
             error=TRUE, debug=matrix(nc=2, nr=0),
             verbose=igraph.par("verbose"))
revolver.il (graph, cats, niter=5, agebins=max(vcount(graph)/7100, 10),
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.ir (graph, cats, window, niter=5,
            sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
            error=TRUE, debug=numeric(), verbose=igraph.par("verbose"))
revolver.air (graph, cats, window,
             niter=5, agebins=max(vcount(graph)/7100, 10),
             sd=FALSE, norm=FALSE, cites=FALSE, expected=FALSE,
             error=TRUE, debug=matrix(nc=2, nr=0),
             verbose=igraph.par("verbose"))
revolver.d.d (graph, vtime = V(graph)$time, etime = E(graph)$time, niter = 5, 
             sd = FALSE, norm = FALSE, cites = FALSE, expected = FALSE, 
             error = TRUE, debug = matrix(nc = 2, nr = 0),
             verbose = igraph.par("verbose")) 
revolver.p.p (graph, events = get.graph.attribute(graph, "events"), 
             vtime = V(graph)$time, etime = E(graph)$time, niter = 5, sd = FALSE, 
             norm = FALSE, cites = FALSE, expected = FALSE, error = TRUE, 
             debug = matrix(nc = 2, nr = 0), verbose = igraph.par("verbose"))

Arguments

nodes

kernel

outseq

outdist

m

directed

verbose

graph

niter

sd

norm

cites

expected

error

debug

agebins

cats

window

vtime

etime

events

Value

• A named list.

Details

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