nndist(spatstat)
nndist()所属R语言包：spatstat
Nearest neighbour distances
最近邻距离
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the distance from each point to its nearest neighbour in a point pattern. Alternatively computes the distance to the second nearest neighbour, or third nearest, etc.
计算每个点的距离其最近的邻居在点模式。或者计算的距离，所述第二近邻，或第三最近等
用法----------Usage----------
nndist(X, ...)
## S3 method for class 'ppp'
nndist(X, ..., k=1, method="C")
## Default S3 method:
nndist(X, Y=NULL, ..., k=1, method="C")
参数----------Arguments----------
参数：X,Y
Arguments specifying the locations of a set of points. For nndist.ppp, the argument X should be a point pattern (object of class "ppp"). For nndist.default, typically X and Y would be numeric vectors of equal length. Alternatively Y may be omitted and X may be a list with two components x and y, or a matrix with two columns.
指定的位置的一组点的引数。 nndist.ppp，参数X应该是一个点模式（类的对象"ppp"“）。对于nndist.default，通常X和Y将数字向量的长度相等。或者Y可以省略，并且X可以是带有两个组件的列表x和y，或一个具有两列的矩阵。
参数：...
Ignored by nndist.ppp and nndist.default.
忽略nndist.ppp和nndist.default。
参数：k
Integer, or integer vector. The algorithm will compute the distance to the kth nearest neighbour.
整数或整数向量。该算法计算距离的的k日最近的邻居。
参数：method
String specifying which method of calculation to use. Values are "C" and "interpreted".
字符串，用于指定使用的计算方法。值是"C"和"interpreted"。
Details
详细信息----------Details----------
This function computes the Euclidean distance from each point in a point pattern to its nearest neighbour (the nearest other point of the pattern). If k is specified, it computes the distance to the kth nearest neighbour.
该函数计算其近邻（最接近的其他点的图案）的点图案中的每个点的欧几里得距离。如果k指定，计算距离的的k日最近的邻居。
The function nndist is generic, with a method for point patterns (objects of class "ppp"), and a default method for coordinate vectors. There is also a method for line segment patterns, nndist.psp.
的功能nndist是通用的，与点图案的方法（类"ppp"），以及一个默认的坐标向量的方法的对象。还设有一个线段图案的方法，nndist.psp。
The method for point patterns expects a single point pattern argument X and returns the vector of its nearest neighbour distances.
点模式的方法，预计单点模式的话，X和返回其近邻距离矢量。
The default method expects that X and Y will determine the coordinates of a set of points. Typically X and Y would be numeric vectors of equal length. Alternatively Y may be omitted and X may be a list with two components named x and y, or a matrix or data frame with two columns.
默认的方法，希望这X和Y将确定一组点的坐标。通常情况下X和Y将数字向量的长度相等。或者Y可以省略，并且X可能是一个名为x和y，或具有两列的矩阵或数据框的两个组件列表。
The argument k may be a single integer, or an integer vector. If it is a vector, then the kth nearest neighbour distances are computed for each value of k specified in the vector.
参数k可能是一个整数或整数向量。如果它是一个向量，然后k个近邻距离k向量中指定的每个值的计算。
The argument method is not normally used. It is retained only for checking the validity of the software. If method = "interpreted" then the distances are computed using interpreted R code only. If method="C" (the default) then C code is used. The C code is faster by two to three orders of magnitude and uses much less memory.
参数method不能正常使用。它只会保留检查的软件的有效性。如果method = "interpreted"的距离计算仅使用解释R代码。如果method="C"（默认值），那么C代码使用。 C代码由两到三个数量级，速度更快，占用更少的内存。
If there is only one point (if x has length 1), then a nearest neighbour distance of Inf is returned. If there are no points (if x has length zero) a numeric vector of length zero is returned.
如果只有一个点（如果x具有长度为1），那么一个近邻距离Inf被返回。如果没有点（如果x长度为零的）返回长度为零的一个数值向量。
To identify which point is the nearest neighbour of a given point, use nnwhich.
要确定哪个点是一个给定的点最近的邻居，使用nnwhich。
To use the nearest neighbour distances for statistical inference, it is often advisable to use the edge-corrected empirical distribution, computed by Gest.
要使用统计推断的距离最近的邻居，是经常建议使用边缘校正的经验分布，计算出Gest。
To find the nearest neighbour distances from one point pattern to another point pattern, use nncross.
要找到距离最近的邻居模式从一个点到另一个点的模式，使用nncross。
值----------Value----------
Numeric vector or matrix containing the nearest neighbour distances for each point.
包含近邻的每个点的距离的数值向量或矩阵。
If k = 1 (the default), the return value is a numeric vector v such that v[i] is the nearest neighbour distance for the ith data point.
如果k = 1（默认值），则返回值是一个数值向量v这样v[i]的i个数据点的距离是最近的邻居。
If k is a single integer, then the return value is a numeric vector v such that v[i] is the kth nearest neighbour distance for the ith data point.
如果k是一个整数，则返回值是一个数值向量v等v[i]是k日的最近邻距离i日数据点。
If k is a vector, then the return value is a matrix m such that m[i,j] is the k[j]th nearest neighbour distance for the ith data point.
如果k是一个向量，则返回值是一个矩阵m等m[i,j]是k[j]日最近的邻居i个数据点的距离。
警告----------Warnings----------
An infinite or NA value is returned if the distance is not defined (e.g. if there is only one point in the point pattern).
的无限NA返回值，如果没有被定义的距离（例如，如果只有一个点在点模式）。
（作者）----------Author(s)----------
Pavel Grabarnik
<a href="mailto:pavel.grabar@issp.serpukhov.su">pavel.grabar@issp.serpukhov.su</a>
and
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
参见----------See Also----------
nndist.psp, pairdist, Gest, nnwhich, nncross.
nndist.psp，pairdist，Gest，nnwhich，nncross。
实例----------Examples----------
data(cells)
# nearest neighbours[最近的邻居]
d <- nndist(cells)
# second nearest neighbours[次近邻]
d2 <- nndist(cells, k=2)
# first, second and third nearest[第一，第二和第三最近]
d1to3 <- nndist(cells, k=1:3)
x <- runif(100)
y <- runif(100)
d <- nndist(x, y)
# Stienen diagram[Stienen图]
plot(cells %mark% (nndist(cells)/2), markscale=1)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 13:50:30
