https://github.com/cran/spatstat
Tip revision: 1b6f7ce253524f978d8945645a567ffe709bf90a authored by Adrian Baddeley on 13 October 2016, 01:00:59 UTC
version 1.47-0
version 1.47-0
Tip revision: 1b6f7ce
nndist.ppx.Rd
\name{nndist.ppx}
\alias{nndist.ppx}
\title{Nearest Neighbour Distances in Any Dimensions}
\description{
Computes the distance from each point to its nearest neighbour
in a multi-dimensional point pattern.
Alternatively computes the distance to the
second nearest neighbour, or third nearest, etc.
}
\usage{
\method{nndist}{ppx}(X, \dots, k=1)
}
\arguments{
\item{X}{
Multi-dimensional point pattern
(object of class \code{"ppx"}).
}
\item{\dots}{
Arguments passed to \code{\link{coords.ppx}} to determine
which coordinates should be used.
}
\item{k}{
Integer, or integer vector. The algorithm will compute the distance to the
\code{k}th nearest neighbour.
}
}
\value{
Numeric vector or matrix containing the
nearest neighbour distances for each point.
If \code{k = 1} (the default), the return value is a
numeric vector \code{v} such that \code{v[i]} is the
nearest neighbour distance for the \code{i}th data point.
If \code{k} is a single integer, then the return value is a
numeric vector \code{v} such that \code{v[i]} is the
\code{k}th nearest neighbour distance for the
\code{i}th data point.
If \code{k} is a vector, then the return value is a
matrix \code{m} such that \code{m[i,j]} is the
\code{k[j]}th nearest neighbour distance for the
\code{i}th data point.
}
\details{
This function computes the Euclidean distance from each point
in a multi-dimensional
point pattern to its nearest neighbour (the nearest other
point of the pattern). If \code{k} is specified, it computes the
distance to the \code{k}th nearest neighbour.
The function \code{nndist} is generic; this function
\code{nndist.ppx} is the method for the class \code{"ppx"}.
The argument \code{k} may be a single integer, or an integer vector.
If it is a vector, then the \eqn{k}th nearest neighbour distances are
computed for each value of \eqn{k} specified in the vector.
If there is only one point (if \code{x} has length 1),
then a nearest neighbour distance of \code{Inf} is returned.
If there are no points (if \code{x} has length zero)
a numeric vector of length zero is returned.
To identify \emph{which} point is the nearest neighbour of a given point,
use \code{\link{nnwhich}}.
To find the nearest neighbour distances from one point pattern
to another point pattern, use \code{\link{nncross}}.
By default, both spatial and temporal coordinates are extracted.
To obtain the spatial distance between points in a space-time point
pattern, set \code{temporal=FALSE}.
}
\section{Warnings}{
An infinite or \code{NA} value is returned if the
distance is not defined (e.g. if there is only one point
in the point pattern).
}
\seealso{
\code{\link{nndist}},
\code{\link{pairdist}},
\code{\link{nnwhich}}
}
\examples{
df <- data.frame(x=runif(5),y=runif(5),z=runif(5),w=runif(5))
X <- ppx(data=df)
# nearest neighbours
d <- nndist(X)
# second nearest neighbours
d2 <- nndist(X, k=2)
# first, second and third nearest
d1to3 <- nndist(X, k=1:3)
}
\author{
\adrian
}
\keyword{spatial}
\keyword{math}