% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/network-summary.R
\name{network_rich_club}
\alias{network_rich_club}
\title{Rich Club Coefficient}
\usage{
network_rich_club(x, k = NULL, normalized = FALSE, n_random = 10, ...)
}
\arguments{
\item{x}{Network input: matrix, igraph, network, cograph_network, or tna object}

\item{k}{Degree threshold. Only nodes with degree > k are included.
If NULL, uses median degree.}

\item{normalized}{Logical. Normalize by random graph expectation? Default FALSE.}

\item{n_random}{Number of random graphs for normalization. Default 10.}

\item{...}{Additional arguments passed to \code{\link{to_igraph}}}
}
\value{
Numeric: rich club coefficient (> 1 indicates rich club effect when normalized)
}
\description{
Computes the rich club coefficient for a given degree threshold k.
Measures the tendency of high-degree nodes to connect to each other.
A normalized version compares to random graphs.
}
\examples{
# Scale-free networks often show rich-club effect
if (requireNamespace("igraph", quietly = TRUE)) {
  g <- igraph::barabasi.game(50, m = 2)
  network_rich_club(g, k = 5)
}
}
