voronoi-package(voronoi)
voronoi-package()所属R语言包:voronoi
Methods and applications related to Voronoi tessellations
相关的Voronoi镶嵌的方法及应用
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Methods and applications related to Voronoi tessellations
相关的Voronoi镶嵌的方法及应用
Details
详细信息----------Details----------
</table>
</ TABLE>
(作者)----------Author(s)----------
Christopher D. Barr, Travis A. Gerke, David M. Diez
Maintainer: Christopher D. Barr <cdbarr@gmail.com>
参考文献----------References----------
C.D Barr and F.P Schoenberg. On the Voronoi Estimator for the Intensity of an Inhomogeneous Planar Poisson Process. Biometrika, 1:1-15, 2010.
Q. Du, V. Faber and M. Gunzburger. Centroidal Voronoi Tesselations: Applications and Algorithms. SIAM Review 41:637-676, 1999.
C.G. Wager, B.A. Coull and N. Lange. Modelling Spatial Intensity for Replicated Inhomogeneous Point Patterns in Brain Imaging. J.R. Statist. Soc. B, 66:429-446, 2004.
参见----------See Also----------
ve, centroidal, pattern.sim, voronoi.game
ve,centroidal,pattern.sim,voronoi.game
实例----------Examples----------
#=====> ve <=====#[=====> VE <=====#]
p <- pattern.sim(7, type='moon')
t5 <- ve(p, rw=c(0,1,0,1))
plot(t5)
points(t5, cex=0.2)
#=====> centroidal <=====#[=>质心<=====#]
f <- function(x, y) x^4 + y^4
antideriv.x <- function(x, y) x^5/5 + x*y^4
antideriv.y <- function(x, y) y*x^4 + y^5/5
obj <- deldir(runif(10), runif(10))
c.obj <- centroidal(x = obj, eps = .005, f = f,
antideriv.x = antideriv.x,
antideriv.y = antideriv.y,
divisions = 10, verbose = 5)
par(mfrow=c(1,2))
plot(obj, wlines="tess", main="Original Tessellation")
plot(c.obj$T, wlines="tess", main="Centroidal Tessellation")
#=====> pattern.sim <=====#[=> pattern.sim <=====#]
par(mfrow = c(2,2))
plot(pattern.sim(type = "linear"), main = "linear")
plot(pattern.sim(type = "quadratic"), main = "quadratic")
plot(pattern.sim(type = "moon"), main = "moon")
plot(pattern.sim(type = "ridge"), main = "ridge")
for(i in 1:4) {
plot(pattern.sim(i + 6, type = "moon"),
main = paste("r = ", i + 6), pch = 20, cex = 0.2)
}
for(i in 1:4) {
plot(pattern.sim(i + 6, type = "ridge"),
main = paste("r = ", i + 6), pch = 20, cex = 0.2)
}
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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