% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/centrality.R
\name{centrality_dmnc}
\alias{centrality_dmnc}
\title{Density of Maximum Neighborhood Component (DMNC)}
\usage{
centrality_dmnc(x, mode = "all", dmnc_epsilon = 1.7, ...)
}
\arguments{
\item{x}{Network input (matrix, igraph, network, cograph_network, tna object).}

\item{mode}{For directed networks: \code{"all"} (default), \code{"in"}, or
\code{"out"}.}

\item{dmnc_epsilon}{Numeric. Epsilon exponent for DMNC. Default 1.7 as
recommended by Lin et al. (2008). centiserve uses 1.67 (four-community
assumption). Must be between 1 and 2.}

\item{...}{Additional arguments passed to \code{\link{centrality}} (e.g.,
\code{normalized}, \code{weighted}, \code{directed}).}
}
\value{
Named numeric vector of DMNC values.
}
\description{
Edge count divided by max component size^1.5 in the neighborhood subgraph.
}
\examples{
adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), 3, 3)
rownames(adj) <- colnames(adj) <- c("A", "B", "C")
centrality_dmnc(adj)
}
\seealso{
\code{\link{centrality}} for computing multiple measures at once,
\code{\link{centrality_mnc}} for the size-only variant.
}
