% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fit.R
\name{power.law.fit}
\alias{power.law.fit}
\title{Fitting a power-law distribution function to discrete data}
\usage{
power.law.fit(
  x,
  xmin = NULL,
  start = 2,
  force.continuous = FALSE,
  implementation = c("plfit", "R.mle"),
  ...
)
}
\arguments{
\item{x}{The data to fit, a numeric vector. For implementation
\sQuote{\code{R.mle}} the data must be integer values. For the
\sQuote{\code{plfit}} implementation non-integer values might be present and
then a continuous power-law distribution is fitted.}

\item{xmin}{Numeric scalar, or \code{NULL}. The lower bound for fitting the
power-law. If \code{NULL}, the smallest value in \code{x} will be used for
the \sQuote{\code{R.mle}} implementation, and its value will be
automatically determined for the \sQuote{\code{plfit}} implementation. This
argument makes it possible to fit only the tail of the distribution.}

\item{start}{Numeric scalar. The initial value of the exponent for the
minimizing function, for the \sQuote{\code{R.mle}} implementation. Usually
it is safe to leave this untouched.}

\item{force.continuous}{Logical scalar. Whether to force a continuous
distribution for the \sQuote{\code{plfit}} implementation, even if the
sample vector contains integer values only (by chance). If this argument is
false, igraph will assume a continuous distribution if at least one sample
is non-integer and assume a discrete distribution otherwise.}

\item{implementation}{Character scalar. Which implementation to use. See
details below.}

\item{...}{Additional arguments, passed to the maximum likelihood
optimizing function, \code{\link[stats4:mle]{stats4::mle()}}, if the \sQuote{\code{R.mle}}
implementation is chosen. It is ignored by the \sQuote{\code{plfit}}
implementation.}
}
\description{
\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}

\code{power.law.fit()} was renamed to \code{\link[=fit_power_law]{fit_power_law()}} to create a more
consistent API.
}
\keyword{internal}
