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% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/games.R
\name{sample_traits_callaway}
\alias{callaway.traits.game}
\alias{establishment.game}
\alias{sample_traits}
\alias{sample_traits_callaway}
\alias{traits}
\alias{traits_callaway}
\title{Graph generation based on different vertex types}
\usage{
sample_traits_callaway(nodes, types, edge.per.step = 1, type.dist = rep(1,
types), pref.matrix = matrix(1, types, types), directed = FALSE)
traits_callaway(...)
sample_traits(nodes, types, k = 1, type.dist = rep(1, types),
pref.matrix = matrix(1, types, types), directed = FALSE)
traits(...)
}
\arguments{
\item{nodes}{The number of vertices in the graph.}
\item{types}{The number of different vertex types.}
\item{edge.per.step}{The number of edges to add to the graph per time step.}
\item{type.dist}{The distribution of the vertex types. This is assumed to be
stationary in time.}
\item{pref.matrix}{A matrix giving the preferences of the given vertex
types. These should be probabilities, ie. numbers between zero and one.}
\item{directed}{Logical constant, whether to generate directed graphs.}
\item{...}{Passed to the constructor, \code{sample_traits} or
\code{sample_traits_callaway}.}
\item{k}{The number of trials per time step, see details below.}
}
\value{
A new graph object.
}
\description{
These functions implement evolving network models based on different vertex
types.
}
\details{
For \code{sample_traits_callaway} the simulation goes like this: in each
discrete time step a new vertex is added to the graph. The type of this
vertex is generated based on \code{type.dist}. Then two vertices are
selected uniformly randomly from the graph. The probability that they will
be connected depends on the types of these vertices and is taken from
\code{pref.matrix}. Then another two vertices are selected and this is
repeated \code{edges.per.step} times in each time step.
For \code{sample_traits} the simulation goes like this: a single vertex is
added at each time step. This new vertex tries to connect to \code{k}
vertices in the graph. The probability that such a connection is realized
depends on the types of the vertices involved and is taken from
\code{pref.matrix}.
}
\examples{
# two types of vertices, they like only themselves
g1 <- sample_traits_callaway(1000, 2, pref.matrix=matrix( c(1,0,0,1), nc=2))
g2 <- sample_traits(1000, 2, k=2, pref.matrix=matrix( c(1,0,0,1), nc=2))
}
\author{
Gabor Csardi \email{csardi.gabor@gmail.com}
}
\keyword{graphs}
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