voss1g(Voss)
voss1g()所属R语言包:Voss
Fractal Brownian function on 1D grid with a generic Voss algorithm
一维网格一个通用沃斯算法的分形函数
译者:生物统计家园网 机器人LoveR
描述----------Description----------
voss1g() function generates realizations of a fractal Brownian function on uniform 1D grid (FBF(x)) with a generic version of the Voss algorithm (random sequential additions).
voss1g()函数生成的分形布朗功能的实现统一1D网格(FBF(X))的的沃斯算法(随机顺序增加)的一个仿制版本。
用法----------Usage----------
voss1g(p=cbind(n=0.5^-seq(0,7)+1,
s=dchisq(seq(0,7), df=2)),
center=TRUE)
参数----------Arguments----------
参数:p
a matrix of parameters:<br> nrow(p) a number of iterations;<br> p[,"n"] a number of partition points in the iteration process;<br> p[,"s"] a standard deviation of normal pseudorandom additions;
参数的矩阵:<br>文章nrow(p)迭代次数; <br>文章p[,"n"]在迭代过程中的分割点; <br>文章p[,"s"]一个标准偏差的一些正常的伪随机补充;
参数:center
logical; if center=TRUE then the y-coordinates of prefractal points will be centered.
逻辑,如果center=TRUE然后y坐标prefractal点将会集中。
Details
详细信息----------Details----------
The Voss algorithm on 1D grid is based on an iterative partitioning of the initial segment into smaller subsegments by linear interpolation of additional points.
沃斯一维网格算法的基础上分割为更小的子段的起始段,通过线性插值的附加点的迭代。
At each iteration, all values of the fractal Brownian function get normal pseudorandom additions with zero mean and standard deviation, which depends on the iteration index s[i].
在每次迭代中,所有的分形布朗功能得到正常的伪随机增加值与零均值和标准差,这取决于迭代指数s[i]。
By default, the iterative distribution of standard deviation in the generic version of the Voss algorithm is equal to the probability density of the chi-square distribution with 2 degrees of freedom: s[i] <- dchisq(i, df=2).
默认情况下,迭代等于2个自由度的卡方分布的概率密度分布的标准偏差在沃斯算法的通用版本是:s[i] <- dchisq(i, df=2)。
值----------Value----------
A list of Cartesian coordinates of prefractal points.
prefractal点的直角坐标列表。
(作者)----------Author(s)----------
Pavel V. Moskalev
参考文献----------References----------
//Technical Physics, Vol.53, No.10 (2008), pp.1261-1266.
参见----------See Also----------
voss2g, voss1d
voss2g,voss1d
实例----------Examples----------
# Example 1: FBF(x) with a s[i]=dchisq(i,df=2)[例1:FBF(x)与一个S [I] = dchisq(I,DF = 2)]
set.seed(20120522)
plot(voss1g(), type="l", xlab="x", ylab="y",
main="FBF(x) with a s[i]=dchisq(i,df=2)")
abline(h=0, lty=2)
# Example 2: FBF(x) with a s[i]=dlnorm(i,sdlog=1)[实施例2(x)的一个则s [i] = dlnorm(ⅰ,sdlog = 1:FBF)]
set.seed(20120522)
voss <- voss1g(p=cbind(n=0.5^-seq(0,7)+1,
s=dlnorm(seq(0,7), sdlog=1)))
plot(voss, type="l", xlab="x", ylab="y",
main="FBF(x) with a s[i]=dlnorm(i,sdlog=1)")
abline(h=0, lty=2)
# Example 3: FBF(x,y) with a s[i]=df(i,df1=7,df2=7)[实施例3:用则s [i] = df的(ⅰ,DF1 = 7,DF2 = 7 FBF(的x,y))]
set.seed(20120522)
voss <- voss1g(p=cbind(n=0.5^-seq(0,7)+1,
s=df(seq(0,7), df1=7, df2=7)))
plot(voss, type="l", xlab="x", ylab="y",
main="FBF(x) with a s[i]=df(i,df1=7,df2=7)")
abline(h=0, lty=2)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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