F3est(spatstat)
F3est()所属R语言包：spatstat
Empty Space Function of a Three-Dimensional Point Pattern
空空间功能的一个三维点模式
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Estimates the empty space function F3(r) from a three-dimensional point pattern.
估计空的空间功能F3(r)一个三维点模式。
用法----------Usage----------
F3est(X, ..., rmax = NULL, nrval = 128, vside = NULL,
correction = c("rs", "km", "cs"),
sphere = c("fudge", "ideal", "digital"))
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 F3(r) will be estimated.
可选。最大的参数值rF3(r)将估计。
参数：nrval
Optional. Number of values of r for which F3(r) will be estimated. A large value of nrval is required to avoid discretisation effects.
可选。 r的F3(r)将估计值数。一个较大的值nrval要求，以避免离散的影响。
参数：vside
Optional. Side length of the voxels in the discrete approximation.
可选。的体素中的离散逼近的边的长度。
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：sphere
Optional. Character string specifying how to calculate the theoretical value of F3(r) for a Poisson process. See Details.
可选。字符串指定如何计算的理论值F3(r)的泊松过程。查看详细信息。
Details
详细信息----------Details----------
For a stationary point process Phi in three-dimensional space, the empty space function is
对于一个固定的点过程Phi在三维空间中，空的空间的函数是
where d(0,Phi) denotes the distance from a fixed origin 0 to the nearest point of Phi.
d(0,Phi)是指从一个固定的起源0的Phi的最近点的距离。
The three-dimensional point pattern X is assumed to be a partial realisation of a stationary point process Phi. The empty space function of Phi can then be estimated using techniques described in the References.
的三维点模式X被认为是一个固定的点过程Phi部分实现。空空间功能的Phi然后可以在参考文献中描述的技术估计。
The box containing the point pattern is discretised into cubic voxels of side length vside. The distance function d(u,Phi) is computed for every voxel centre point u using a three-dimensional version of the distance transform algorithm (Borgefors, 1986). The empirical cumulative distribution function of these values, with appropriate edge corrections, is the estimate of F3(r).
箱点模式离散化到立方米像素的边长vside。距离函数d(u,Phi)为每个体素的中心点u使用一个三维版本的距离变换算法（Borgefors，1986）计算。这些值的经验累积分布函数，适当的边缘修正，估计F3(r)。
The available edge corrections are:
边缘修正：
the reduced sample (aka minus sampling, border correction) estimator (Baddeley et al, 1993)
减少样品（又名减采样，边框校正）估计（巴德利等，1993）
the three-dimensional version of the Kaplan-Meier estimator (Baddeley and Gill, 1997)
三维版本的Kaplan-Meier估计（Baddeley和吉尔，1997年）
the three-dimensional generalisation of the Chiu-Stoyan or Hanisch estimator (Chiu and Stoyan, 1998).
三维概括邱，斯托扬或Hanisch估计的（邱和斯托扬，1998年）。
The result includes a column theo giving the theoretical value of F3(r) for a uniform Poisson process (Complete Spatial Randomness). This value depends on the volume of the sphere of radius r measured in the discretised distance metric. The argument sphere determines how this will be calculated.
结果中包括一列theo的理论值F3(r)一个统一的泊松过程（完整的空间随机性）。该值依赖于半径的球体的体积r测定的离散化的距离度量。这将如何计算的参数sphere决定。
If sphere="ideal" the calculation will use the volume of an ideal sphere of radius r namely (4/3) * pi * r^3. This is not recommended because the theoretical values of F3(r) are inaccurate.
如果sphere="ideal"，计算将使用量的理想球体的半径r即(4/3) * pi * r^3。这是不建议，因为理论值F3(r)是不准确的。
If sphere="fudge" then the volume of the ideal sphere will be multiplied by 0.78, which gives the approximate volume of the sphere in the discretised distance metric.
如果sphere="fudge"然后理想的球体的体积将被乘以0.78，它给出了近似体积的球体中的离散化的距离度量。
If sphere="digital" then the volume of the sphere in the discretised distance metric is computed exactly using another distance transform. This takes longer to compute, but is exact.
如果sphere="digital"然后在离散化的距离度量的球体的体积被精确计算使用另一个距离变换。这需要更长的时间来计算，但是精确的。
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"）。
警告----------Warnings----------
A small value of vside and a large value of nrval are required for reasonable accuracy.
一个较小的值vside和nrval一个较大的值所需要的合理的精度。
The default value of vside ensures that the total number of voxels is 2^22 or about 4 million. To change the default number of voxels, see spatstat.options("nvoxel").
的默认值vside确保总人数的像素是2^22或约400万。要更改默认的像素数量，请参阅spatstat.options("nvoxel")。
（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 (1993) 641–668.
Kaplan-Meier estimators of interpoint distance distributions for spatial point processes. Annals of Statistics 25, 263–292.
Distance transformations in digital images. Computer Vision, Graphics and Image Processing 34, 344–371.
Estimators of distance distributions for spatial patterns. Statistica Neerlandica 52, 239–246.
参见----------See Also----------
G3est, K3est, pcf3est.
G3est，K3est，pcf3est。
实例----------Examples----------
X <- rpoispp3(42)
Z <- F3est(X)
if(interactive()) plot(Z)
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 13:28:40
