igraph (version 0.5.1)

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, st=FALSE, 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")) revolver.error.d (graph, kernel) revolver.error.ad (graph, kernel) revolver.error.ade (graph, kernel, cats) revolver.error.adi (graph, kernel, cats) revolver.error.air (graph, kernel, cats, window) revolver.error.ar (graph, kernel, window) revolver.error.de (graph, kernel, cats) revolver.error.di (graph, kernel, cats) revolver.error.dl (graph, kernel) revolver.error.e (graph, kernel, cats) revolver.error.el (graph, kernel, cats) revolver.error.il (graph, kernel, cats) revolver.error.ir (graph, kernel, cats, window) revolver.error.l (graph, kernel) revolver.error.r (graph, kernel, window)

revolver.ml.ade (graph, niter, cats, agebins = 300, delta = 1e-10, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.d (graph, niter, delta = 1e-10, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.de (graph, niter, cats, delta = 1e-10, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.df (graph, niter, delta = 1e-10, verbose = igraph.par("verbose")) revolver.ml.f (graph, niter, delta = 1e-10, verbose = igraph.par("verbose")) revolver.ml.l (graph, niter, agebins = 300, delta = 1e-10)

revolver.ml.AD.alpha.a.beta (graph, alpha, a, beta, abstol = 1e-08, reltol = 1e-08, maxit = 1000, agebins = 300, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.AD.dpareto (graph, alpha, a, paralpha, parbeta, parscale, abstol = 1e-08, reltol = 1e-08, maxit = 1000, agebins = 300, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.ADE.alpha.a.beta (graph, cats, alpha, a, beta, coeffs, abstol = 1e-08, reltol = 1e-08, maxit = 1000, agebins = 300, filter = NULL) revolver.ml.ADE.dpareto (graph, cats, alpha, a, paralpha, parbeta, parscale, coeffs, abstol = 1e-08, reltol = 1e-08, maxit = 1000, agebins = 300, filter = NULL) revolver.ml.D.alpha (graph, alpha, abstol = 1e-08, reltol = 1e-08, maxit = 1000, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.D.alpha.a (graph, alpha, a, abstol = 1e-08, reltol = 1e-08, maxit = 1000, filter = NULL, verbose = igraph.par("verbose")) revolver.ml.DE.alpha.a (graph, cats, alpha, a, coeffs, abstol = 1e-08, reltol = 1e-08, maxit = 1000, filter = NULL)

revolver.ml.AD.dpareto.eval (graph, alpha, a, paralpha, parbeta, parscale, agebins = 300, filter = NULL) revolver.ml.ADE.dpareto.eval (graph, cats, alpha, a, paralpha, parbeta, parscale, coeffs, agebins = 300, filter = NULL) revolver.ml.ADE.dpareto.evalf (graph, cats, par, agebins, filter = NULL)

revolver.probs.ad (graph, kernel, ntk = FALSE) revolver.probs.ade (graph, kernel, cats) revolver.probs.d (graph, kernel, ntk = FALSE) revolver.probs.de (graph, kernel, cats) revolver.probs.ADE.dpareto (graph, par, cats, gcats, agebins)

Arguments

nodes
kernel
outseq
outdist
m
directed
verbose
graph
niter
sd
norm
cites
expected
error
debug
agebins
cats
window
vtime
etime
events
delta
filter
alpha
a
paralpha
parbeta
parscale
abstol
reltol
maxit
beta
coeffs
par
ntk
gcats
st

Value

  • A named list.

Details

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