% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/network-summary.R
\name{network_local_efficiency}
\alias{network_local_efficiency}
\title{Local Efficiency}
\usage{
network_local_efficiency(
  x,
  weights = NULL,
  invert_weights = NULL,
  alpha = 1,
  ...
)
}
\arguments{
\item{x}{Network input: matrix, igraph, network, cograph_network, or tna object}

\item{weights}{Edge weights (NULL for unweighted). Set to NA to ignore existing weights.}

\item{invert_weights}{Logical or NULL. Invert weights so higher weights = shorter
paths? Default NULL which auto-detects: TRUE for tna objects, FALSE otherwise
(matching igraph/sna). Set TRUE for strength/frequency weights (qgraph style).}

\item{alpha}{Numeric. Exponent for weight inversion. Default 1.}

\item{...}{Additional arguments passed to \code{\link{to_igraph}}}
}
\value{
Numeric in [0, 1]: average local efficiency
}
\description{
Computes the average local efficiency across all nodes. Local efficiency
of a node is the global efficiency of its neighborhood subgraph
(excluding the node itself). Measures fault tolerance and local integration.
}
\examples{
# Complete graph: removing any node leaves complete subgraph, so local efficiency = 1
k5 <- matrix(1, 5, 5); diag(k5) <- 0
network_local_efficiency(k5)  # 1

# Star: neighbors not connected to each other
star <- matrix(c(0,1,1,1,1, 1,0,0,0,0, 1,0,0,0,0, 1,0,0,0,0, 1,0,0,0,0), 5, 5)
network_local_efficiency(star)  # 0
}
