clarkevans(spatstat)
clarkevans()所属R语言包：spatstat
Clark and Evans Aggregation Index
克拉克和Evans聚集指数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the Clark and Evans aggregation index R for a spatial point pattern.
计算的克拉克和埃文斯聚集指数R的空间点格局。
用法----------Usage----------
clarkevans(X, correction=c("none", "Donnelly", "cdf"),
clipregion=NULL)
参数----------Arguments----------
参数：X
A spatial point pattern (object of class "ppp").
一个空间点模式（类的对象"ppp"）。
参数：correction
Character vector. The type of edge correction(s) to be applied.
字符向量。边缘校正的类型（s）到被应用。
参数：clipregion
Clipping region for the guard area correction. A window (object of class "owin"). See Details.
保护区调整的裁剪区域。一个窗口（类的对象"owin"“）。查看详细信息。
Details
详细信息----------Details----------
The Clark and Evans (1954) aggregation index R is a crude measure of clustering or ordering of a point pattern. It is the ratio of the observed mean nearest neighbour distance in the pattern to that expected for a Poisson point process of the same intensity. A value R>1 suggests ordering, while R<1 suggests clustering.
的克拉克和Evans（1954）的聚集指数R是一个粗略的衡量聚类的点模式或订购。它是所观察到的平均预期相同的强度的泊松点过程的模式中的最近邻距离的比率。值R>1建议订货，而R<1显示聚类。
Without correction for edge effects, the value of R will be positively biased. Edge effects arise because, for a point of X close to the edge of the window, the true nearest neighbour may actually lie outside the window. Hence observed nearest neighbour distances tend to be larger than the true nearest neighbour distances.
没有边缘效应的修正，R将积极失之偏颇。边缘效应出现真正的最近的邻居，因为点X靠近窗口的边缘，实际上可能不在窗口。因此，观察到的近邻的距离倾向于是大于真实近邻距离。
The argument correction specifies an edge correction or several edge corrections to be applied. It is a character vector containing one or more of the options "none", "Donnelly", "guard" and "cdf" (which are recognised by partial matching). These edge corrections are:
参数correction指定边缘校正或多个边缘加以更正应用。这是一个字符向量，包含一个或多个选项"none"，"Donnelly"，"guard"和"cdf"（所承认的部分匹配）。这些边缘更正如下：
No edge correction is applied.
·完全没有边缘的校正被施加。
Edge correction of Donnelly (1978), available for rectangular windows only. The theoretical expected value of mean nearest neighbour distance under a Poisson process is adjusted for edge effects by the edge correction of Donnelly (1978). The value of R is the ratio of the observed mean nearest neighbour distance to this adjusted theoretical mean.
唐纳利（1978年）的边缘校正，可用于矩形窗口只。根据一个泊松过程平均近邻距离的理论预期值被调整以作边缘效应唐纳利（1978）的边缘校正。的值R是所观察到的平均近邻距离，该调整后的理论平均的比率。
Guard region or buffer area method. The observed mean nearest neighbour distance for the point pattern X is re-defined by averaging only over those points of X that fall inside the sub-window clipregion.
保护区或缓冲区的方法。所观察到的平均最近邻距离点模式X被重新定义，平均只能通过这些点里面的子窗口X的clipregion那年秋天。
Cumulative Distribution Function method. The nearest neighbour distance distribution function G(r) of the stationary point process is estimated by Gest using the Kaplan-Meier type edge correction. Then the mean of the distribution is calculated from the cdf.
累积分布函数的方法。最近邻距离分布函数G(r)的固定点估计Gest使用Kaplan-Meier生存型边缘校正。然后，计算的平均分布的累积分布函数。
If the argument clipregion is given, then the selected edge corrections will be assumed to include correction="guard".
如果参数clipregion，然后将选定的边修正假设包括correction="guard"。
To perform a test based on the Clark-Evans index, see clarkevans.test.
要执行测试克拉克 - 埃文斯指数的基础上，看到clarkevans.test。
值----------Value----------
A numeric value or numeric vector, with named components
一个数值或数值向量，由指定组件
参数：naive
R without edge correction
R无边缘校正
参数：Donnelly
R using Donnelly edge correction
R使用唐纳利边缘校正
参数：guard
R using guard region
R使用后卫区域的
参数：cdf
R using cdf method
R使用CDF方法
(as selected by correction). The value of the Donnelly component will be NA if the window of X is not a rectangle.
（所选择correction）。 Donnelly组件的值将NAX如果窗口是不是一个矩形。
（作者）----------Author(s)----------
John Rudge
<a href="mailto:rudge@esc.cam.ac.uk">rudge@esc.cam.ac.uk</a>
with modifications by
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>
参考文献----------References----------
Distance to nearest neighbour as a measure of spatial relationships in populations Ecology 35, 445–453.
and edge-effect of total nearest neighbour distance. In Simulation methods in archaeology, Cambridge University Press, pp 91–95.
参见----------See Also----------
clarkevans.test, nndist, Gest
clarkevans.test，nndist，Gest
实例----------Examples----------
# Example of a clustered pattern[在聚类模式的示例]
data(redwood)
clarkevans(redwood)
# Example of an ordered pattern[的有序模式的例子]
data(cells)
clarkevans(cells)
# Random pattern[随机模式]
X <- rpoispp(100)
clarkevans(X)
# How to specify a clipping region[如何指定的裁剪区域]
clip1 <- owin(c(0.1,0.9),c(0.1,0.9))
clip2 <- erosion(cells$window, 0.1)
clarkevans(cells, clipregion=clip1)
clarkevans(cells, clipregion=clip2)
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。
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发表于 2012-9-30 13:16:28
