StraussHard(spatstat)
StraussHard()所属R语言包：spatstat
The Strauss / Hard Core Point Process Model
施特劳斯/硬核点过程模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Creates an instance of the “Strauss/ hard core” point process model which can then be fitted to point pattern data.
“施特劳斯/硬核心”点过程模型，然后可以配点模式数据创建一个实例。
用法----------Usage----------
StraussHard(r, hc)
参数----------Arguments----------
参数：r
The interaction radius of the Strauss interaction
施特劳斯互动的相互作用半径
参数：hc
The hard core distance
硬核的距离
Details
详细信息----------Details----------
A Strauss/hard core process with interaction radius r, hard core distance h < r, and parameters beta and gamma, is a pairwise interaction point process in which
施特劳斯/硬核过程的相互作用半径r，硬核的距离h < r，参数beta和gamma，是一对相互作用点的过程中，
distinct points are not allowed to come closer than a distance h apart
不同点是不允许更近的距离h除了
each pair of points closer than r units apart contributes a factor gamma to the probability density.
每对点接近比r单位除了贡献的因素gamma的概率密度。
This is a hybrid of the Strauss process and the hard core process.
这是一种混合的施特劳斯过程中的硬核过程。
The probability density is zero if any pair of points is closer than h units apart, and otherwise equals
的概率密度是零，如果任何一对点是接近h单位外，否则等于
where x[1],…,x[n] represent the points of the pattern, n(x) is the number of points in the pattern, s(x) is the number of distinct unordered pairs of points that are closer than r units apart, and alpha is the normalising constant.
x[1],…,x[n]代表的模式，n(x)是模式中的点的数量，s(x)是多少的点，比r的不同无序对单位外，和alpha是的标准化不变。
The interaction parameter gamma may take any positive value (unlike the case for the Strauss process). If gamma = 1, the process reduces to a classical hard core process. If gamma < 1, the model describes an “ordered” or “inhibitive” pattern. If gamma > 1, the model is “ordered” or “inhibitive” up to the distance h, but has an “attraction” between points lying at distances in the range between h and r.
相互作用参数gamma可以采取任何积极的值（与施特劳斯进程的情况下）。如果gamma = 1，过程减少到经典的硬核的过程。如果gamma < 1，该模型描述的“有序”或“抑制”的格局。如果gamma > 1，该模型是“有序”或“抑制”的距离h，但点之间的距离范围内h之间有一个“景点”和r。
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 Strauss/hard core process pairwise interaction is yielded by the function StraussHard(). 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。施特劳斯/硬核的过程中对相互作用产生的功能StraussHard()适当的描述。请参见下面的例子。
The canonical parameter log(gamma) is estimated by ppm(), not fixed in StraussHard().
标准参数log(gamma)估计ppm()，而不是固定在StraussHard()。
值----------Value----------
An object of class "interact" describing the interpoint interaction structure of the “Strauss/hard core” process with Strauss interaction radius r and hard core distance hc.
类的一个对象"interact"描述INTERPOINT互动的“施特劳斯/硬核”的过程与结构施特劳斯互动半径r和硬核的距离hc。
（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----------
Practical maximum pseudolikelihood for spatial point patterns. Australian and New Zealand Journal of Statistics 42, 283–322.
Spatial statistics. John Wiley and Sons.
A model for clustering. Biometrika 63, 467–475.
参见----------See Also----------
ppm, pairwise.family, ppm.object
ppm，pairwise.family，ppm.object
实例----------Examples----------
StraussHard(r=1,hc=0.02)
# prints a sensible description of itself[打印本身就是一个明智的描述]
data(cells)
## Not run: [＃不运行：]
ppm(cells, ~1, StraussHard(r=0.1, hc=0.05))
# fit the stationary Strauss/hard core process to `cells'[适合固定的史特劳斯/硬核单元]
## End(Not run)[＃（不执行）]
ppm(cells, ~ polynom(x,y,3), StraussHard(r=0.1, hc=0.05))
# fit a nonstationary Strauss/hard core process[适合非平稳施特劳斯/硬核过程]
# with log-cubic polynomial trend[数三次多项式趋势]
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 14:16:22
