pcf3est(spatstat)
pcf3est()所属R语言包:spatstat
Pair Correlation Function of a Three-Dimensional Point Pattern
对相关函数的一个三维点模式
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Estimates the pair correlation function from a three-dimensional point pattern.
估计对相关函数从一个三维点模式。
用法----------Usage----------
pcf3est(X, ..., rmax = NULL, nrval = 128, correction = c("translation",
"isotropic"), delta=NULL, adjust=1, biascorrect=TRUE)
参数----------Arguments----------
参数:X
Three-dimensional point pattern (object of class "pp3").
三维点的模式(对象类"pp3")。
参数:...
Ignored.
忽略。
参数:rmax
Optional. Maximum value of argument r for which g3(r) will be estimated.
可选。最大的参数值rg3(r)将估计。
参数:nrval
Optional. Number of values of r for which g3(r) will be estimated.
可选。 r的g3(r)将估计值数。
参数:correction
Optional. Character vector specifying the edge correction(s) to be applied. See Details.
可选。字符向量指定的边缘校正(S)。查看详细信息。
参数:delta
Optional. Half-width of the Epanechnikov smoothing kernel.
可选。半宽度的叶帕涅奇尼科夫平滑内核。
参数:adjust
Optional. Adjustment factor for the default value of delta.
可选。调整因素的默认值delta。
参数:biascorrect
Logical value. Whether to correct for underestimation due to truncation of the kernel near r=0.
逻辑值。无论是由于截断的内核附近r=0纠正低估。
Details
详细信息----------Details----------
For a stationary point process Phi in three-dimensional space, the pair correlation function is
对于一个固定的点过程Phi在三维空间中,对相关函数是
where K3' is the derivative of the three-dimensional K-function (see K3est).
其中K3'是三维K-函数(见K3est衍生物)。
The three-dimensional point pattern X is assumed to be a partial realisation of a stationary point process Phi. The distance between each pair of distinct points is computed. Kernel smoothing is applied to these distance values (weighted by an edge correction factor) and the result is renormalised to give the estimate of g3(r).
的三维点模式X被认为是一个固定的点过程Phi部分实现。每对不同的点之间的距离被计算出来。被施加到这些距离值(加权的边缘校正因子)核平滑,结果renormalised给估计g3(r)。
The available edge corrections are:
边缘修正:
the Ohser translation correction estimator (Ohser, 1983; Baddeley et al, 1993)
Ohser翻译校正估计器(Ohser,1983;巴德利等人,1993)
the three-dimensional counterpart of Ripley's isotropic edge correction (Ripley, 1977; Baddeley et al, 1993).
三维对应雷普利各向同性的边缘校正(雷普利,1977;巴德利等人,1993)。
Kernel smoothing is performed using the Epanechnikov kernel with half-width delta. If delta is missing, the default is to use the rule-of-thumb delta = 0.26/lambda^(1/3) where lambda = n/v is the estimated intensity, computed from the number n of data points and the volume v of the enclosing box. This default value of delta is multiplied by the factor adjust.
核平滑半宽度delta叶帕涅奇尼科夫内核使用。 delta如果缺少,默认是使用规则的拇指delta = 0.26/lambda^(1/3)lambda = n/v强度的估计,从数n的数据点和计算量v封闭框。此默认值delta乘以因素adjust的。
The smoothing estimate of the pair correlation g3(r) is typically an underestimate when r is small, due to truncation of the kernel at r=0. If biascorrect=TRUE, the smoothed estimate is approximately adjusted for this bias. This is advisable whenever the dataset contains a sufficiently large number of points.
平滑估计,对相关g3(r)通常是低估当r是小,由于内核在r=0截断的。如果biascorrect=TRUE,平滑的估计大约是这种偏见调整。每当数据集包含足够大量的点,这是可取的。
值----------Value----------
A function value table (object of class "fv") that can be plotted, printed or coerced to a data frame containing the function values.
,可以绘制,打印或强制转换为一个数据框包含的函数值的函数值表(对象类"fv")。
Additionally the value of delta is returned as an attribute of this object.
此外,delta返回这个对象的属性。
(作者)----------Author(s)----------
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>
and Rana Moyeed.
参考文献----------References----------
Analysis of a three-dimensional point pattern with replication. Applied Statistics 42, 641–668.
On estimators for the reduced second moment measure of point processes. Mathematische Operationsforschung und Statistik, series Statistics, 14, 63 – 71.
Modelling spatial patterns (with discussion). Journal of the Royal Statistical Society, Series B, 39, 172 – 212.
参见----------See Also----------
K3est, pcf
K3est,pcf
实例----------Examples----------
X <- rpoispp3(250)
Z <- pcf3est(X)
Zbias <- pcf3est(X, biascorrect=FALSE)
if(interactive()) {
opa <- par(mfrow=c(1,2))
plot(Z, ylim.covers=c(0, 1.2))
plot(Zbias, ylim.covers=c(0, 1.2))
par(opa)
}
attr(Z, "delta")
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。
|