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% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/structural.properties.R
\name{knn}
\alias{graph.knn}
\alias{knn}
\title{Average nearest neighbor degree}
\usage{
knn(graph, vids = V(graph), weights = NULL)
}
\arguments{
\item{graph}{The input graph. It can be directed, but it will be treated as
undirected, i.e. the direction of the edges is ignored.}
\item{vids}{The vertices for which the calculation is performed. Normally it
includes all vertices. Note, that if not all vertices are given here, then
both \sQuote{\code{knn}} and \sQuote{\code{knnk}} will be calculated based
on the given vertices only.}
\item{weights}{Weight vector. If the graph has a \code{weight} edge
attribute, then this is used by default. If this argument is given, then
vertex strength (see \code{\link{strength}}) is used instead of vertex
degree. But note that \code{knnk} is still given in the function of the
normal vertex degree.}
}
\value{
A list with two members: \item{knn}{A numeric vector giving the
average nearest neighbor degree for all vertices in \code{vids}.}
\item{knnk}{A numeric vector, its length is the maximum (total) vertex
degree in the graph. The first element is the average nearest neighbor
degree of vertices with degree one, etc. }
}
\description{
Calculate the average nearest neighbor degree of the given vertices and the
same quantity in the function of vertex degree
}
\details{
Note that for zero degree vertices the answer in \sQuote{\code{knn}} is
\code{NaN} (zero divided by zero), the same is true for \sQuote{\code{knnk}}
if a given degree never appears in the network.
}
\examples{
# Some trivial ones
g <- make_ring(10)
knn(g)
g2 <- make_star(10)
knn(g2)
# A scale-free one, try to plot 'knnk'
g3 <- sample_pa(1000, m=5)
knn(g3)
# A random graph
g4 <- sample_gnp(1000, p=5/1000)
knn(g4)
# A weighted graph
g5 <- make_star(10)
E(g5)$weight <- seq(ecount(g5))
knn(g5)
}
\author{
Gabor Csardi \email{csardi.gabor@gmail.com}
}
\references{
Alain Barrat, Marc Barthelemy, Romualdo Pastor-Satorras,
Alessandro Vespignani: The architecture of complex weighted networks, Proc.
Natl. Acad. Sci. USA 101, 3747 (2004)
}
\keyword{graphs}
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