Geyer(spatstat)
Geyer()所属R语言包：spatstat
Geyer's Saturation Point Process Model
盖尔的饱和点过程模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Creates an instance of Geyer's saturation point process model which can then be fitted to point pattern data.
盖尔的饱和点过程模型，然后可以配点模式的数据创建一个实例。
用法----------Usage----------
Geyer(r,sat)
参数----------Arguments----------
参数：r
Interaction radius. A positive real number.
互动半径。一个正实数。
参数：sat
Saturation threshold. A positive real number.
饱和阈值。一个正实数。
Details
详细信息----------Details----------
Geyer (1999) introduced the “saturation process”, a modification of the Strauss process (see Strauss) in which the total contribution to the potential from each point (from its pairwise interaction with all other points) is trimmed to a maximum value s. This model is implemented in the function Geyer().
“赫耶尔”（1999）介绍了“饱和过程”，施特劳斯过程的变形例（见Strauss），其中每一个点的电位从（从其对相互作用与所有其他点）的总贡献修整，以一个最大值s。此模型中实现的功能Geyer()。
The saturation point process with interaction radius r, saturation threshold s, and parameters beta and gamma, is the point process in which each point x[i] in the pattern X contributes a factor
饱和点过程与互动半径r，饱和阈值s，参数beta和gamma，是点的过程中，每个点x[i]的模式X贡献的一个因素
to the probability density of the point pattern, where t(x[i],X) denotes the number of "close neighbours" of x[i] in the pattern X. A close neighbour of x[i] is a point x[j] with j != i such that the distance between x[i] and x[j] is less than or equal to r.
到概率密度点模式，其中t(x[i],X)表示“近邻”的x[i]的模式X。 x[i]的近邻，是一个点x[j]j != i等之间的距离x[i]和x[j]是小于或等于r的。
If the saturation threshold s is set to infinity, this model reduces to the Strauss process (see Strauss) with interaction parameter gamma^2. If s = 0, the model reduces to the Poisson point process. If s is a finite positive number, then the interaction parameter gamma may take any positive value (unlike the case of the Strauss process), with values gamma < 1 describing an "ordered" or "inhibitive" pattern, and values gamma > 1 describing a "clustered" or "attractive" pattern.
，如果饱和阈值s设置为无穷大，这种模式降低了施特劳斯进程（见Strauss）相互作用参数gamma^2。如果s = 0，模型简化为泊松点过程中。如果s是一个有限的正数，则相互作用参数gamma可以采取任意的正值（不像施特劳斯过程的情况下），与值gamma < 1描述的“有序”或“抑制”的格局，和值gamma > 1描述了一个“聚类”或“有吸引力”的模式。
The nonstationary saturation process is similar except that the value beta is replaced by a function beta(x[i]) of location.
一类非饱和过程是类似的，除了的价值beta被替换为一个功能beta(x[i])的位置。
The function ppm(), which fits point process models to point pattern data, requires an argument of class "interact" describing the interpoint interaction structure of the model to be fitted. The appropriate description of the saturation process interaction is yielded by Geyer(r, sat) where the arguments r and sat specify the Strauss interaction radius r and the saturation threshold s, respectively. See the examples below.
的功能ppm()，适合点模式数据点过程模型，需要一个参数的类"interact"描述INTERPOINT互动结构的模型被安装。适当的描述饱和过程相互作用产生的Geyer(r, sat)这里的参数r和sat指定施特劳斯互动半径r和饱和阈值s分别。请参见下面的例子。
Note the only arguments are the interaction radius r and the saturation threshold sat. When r and sat are fixed, the model becomes an exponential family. The canonical parameters log(beta) and log(gamma) are estimated by ppm(), not fixed in Geyer().
注意：唯一的参数是的相互作用半径r和饱和阈值sat。当r和sat是固定的，该模型成为一个指数家族。规范参数log(beta)和log(gamma)估计ppm()，而不是固定在Geyer()。
值----------Value----------
An object of class "interact" describing the interpoint interaction structure of Geyer's saturation point process with interaction radius r and saturation threshold sat.
类的一个对象"interact"描述INTERPOINT互动的结构与互动半径r盖尔的饱和点的过程和饱和度阈值sat。
（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 Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参考文献----------References----------
Likelihood Inference for Spatial Point Processes. Chapter 3 in O.E. Barndorff-Nielsen, W.S. Kendall and M.N.M. Van Lieshout (eds) Stochastic Geometry: Likelihood and Computation, Chapman and Hall / CRC, Monographs on Statistics and Applied Probability, number 80. Pages 79–140.
参见----------See Also----------
ppm, pairwise.family, ppm.object, Strauss, SatPiece
ppm，pairwise.family，ppm.object，Strauss，SatPiece
实例----------Examples----------
data(cells)
ppm(cells, ~1, Geyer(r=0.07, sat=2))
# fit the stationary saturation process to `cells'[适合固定的饱和过程单元]
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。
|
发表于 2012-9-30 13:31:30
