power.law.fit
fits a power-law distribution to a
data set.power.law.fit(x, xmin=NULL, start=2, force.continuous=FALSE,
implementation=c("plfit", "R.mle"), ...)
R.mle
plfit
NULL
. The lower bound for
fitting the power-law. If NULL
, the smallest value in
x
will be used for the R.mle
R.mle
plfit
mle
, if the
R.mle
plfit
implementation
argument. If it is
R.mle
mle
mle-class
for details. If implementation
is plfit
xmin
were used from the input vector. power.law.fit
provides two maximum likelihood implementations.
If the implementation
argument is R.mle
plfit
The plfit
Aaron Clauset, Cosma R .Shalizi and Mark E.J. Newman: Power-law distributions in empirical data. SIAM Review 51(4):661-703, 2009.
mle
# This should approximately yield the correct exponent 3
g <- barabasi.game(1000) # increase this number to have a better estimate
d <- degree(g, mode="in")
fit1 <- power.law.fit(d+1, 10)
fit2 <- power.law.fit(d+1, 10, implementation="R.mle")
fit1$alpha
coef(fit2)
fit1$logLik
logLik(fit2)
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