rHardcore(spatstat)
rHardcore()所属R语言包:spatstat
Perfect Simulation of the Hardcore Process
完美的模拟性交过程
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Generate a random pattern of points, a simulated realisation of the Hardcore process, using a perfect simulation algorithm.
生成点,模拟实现的性交过程中,使用一个完美的模拟算法的随机图案。
用法----------Usage----------
rHardcore(beta, R = 0, W = owin())
参数----------Arguments----------
参数:beta
intensity parameter (a positive number).
强度参数(正数)。
参数:R
hard core distance (a non-negative number).
硬核的距离(一个非负号)。
参数:W
window (object of class "owin") in which to generate the random pattern. Currently this must be a rectangular window.
窗口(对象类"owin")在其中生成的随机模式。目前,这必须是一个矩形窗口。
Details
详细信息----------Details----------
This function generates a realisation of the Hardcore point process in the window W using a "perfect simulation" algorithm.
这个函数生成一个窗口W使用一个“完美的模拟算法实现的性交点的过程中。
The Hardcore process is a model for strong spatial inhibition. Two points of the process are forbidden to lie closer than R units apart. The Hardcore process is the special case of the Strauss process (see rStrauss) with interaction parameter gamma equal to zero.
性交过程是一个强烈的空间抑制模型。两个点的过程是被禁止的说谎接近R单位除了。性交过程是一个特殊的情况下,的斯特劳斯过程(rStrauss)的相互作用参数gamma等于零的。
The simulation algorithm used to generate the point pattern is "dominated coupling from the past" as implemented by Berthelsen and Moller (2002, 2003). This is a "perfect simulation" or "exact simulation" algorithm, so called because the output of the algorithm is guaranteed to have the correct probability distribution exactly (unlike the Metropolis-Hastings algorithm used in rmh, whose output is only approximately correct).
算法的仿真,用于生成的点图案是“主导从过去的实施Berthelsen和Moller(2002年,2003年)的耦合。这是一个“完美的模拟”或“精确模拟算法,所谓的,因为输出的算法是保证有正确的概率分布完全相同(不同的Metropolis-Hastings算法,其使用rmh,其输出是大约只有正确)。
There is a tiny chance that the algorithm will run out of space before it has terminated. If this occurs, an error message will be generated.
有一个微小的机会,该算法将空间用完之前,它已经终止。如果发生这种情况,将产生一条错误消息。
值----------Value----------
A point pattern (object of class "ppp").
点模式(类的对象"ppp")。
(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>
based on original code for the Strauss process by
Kasper Klitgaard Berthelsen.
参考文献----------References----------
A primer on perfect simulation for spatial point processes. Bulletin of the Brazilian Mathematical Society 33, 351-367.
Likelihood and non-parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling. Scandinavian Journal of Statistics 30, 549-564.
Statistical Inference and Simulation for Spatial Point Processes. Chapman and Hall/CRC.
参见----------See Also----------
rmh, Hardcore, rStrauss, rDiggleGratton.
rmh,Hardcore,rStrauss,rDiggleGratton。
实例----------Examples----------
X <- rHardcore(0.05,1.5,square(141.4))
Z <- rHardcore(100,0.05)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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