% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/centrality.R
\name{centrality_expected_influence_1}
\alias{centrality_expected_influence_1}
\title{Expected Influence (one-step)}
\usage{
centrality_expected_influence_1(x, mode = "out", ...)
}
\arguments{
\item{x}{Network input (matrix, igraph, network, cograph_network, tna
object).}

\item{mode}{One of "all", "in", "out" for directed graphs. Default "out".}

\item{...}{Additional arguments passed to \code{\link{centrality}}.}
}
\value{
Named numeric vector of expected-influence values (signed).
}
\description{
Signed-weight sum of a node's edges (Robinaugh, Millner & McNally 2016).
The appropriate centrality for networks with positive \emph{and} negative
edges (partial-correlation, glasso, signed correlation networks) where
treating negative edges as positive magnitudes can be misleading.
}
\examples{
# Signed weight matrix (partial correlations, for example)
W <- matrix(c( 0.0,  0.5, -0.3,  0.2,
               0.5,  0.0,  0.4, -0.1,
              -0.3,  0.4,  0.0,  0.6,
               0.2, -0.1,  0.6,  0.0), 4, 4, byrow = TRUE)
rownames(W) <- colnames(W) <- c("A", "B", "C", "D")
centrality_expected_influence_1(W)
}
\references{
Robinaugh DJ, Millner AJ, McNally RJ (2016). Identifying
highly influential nodes in the complicated grief network.
\emph{Journal of Abnormal Psychology}, 125(6), 747-757.
}
\seealso{
\code{\link{centrality_expected_influence_2}} for the two-step
variant, \code{\link{centrality_strength}} for the weighted-degree analogue.
}
