fitextcoeff(SpatialExtremes)
fitextcoeff()所属R语言包:SpatialExtremes
Non parametric estimators of the extremal coefficient function
非参数估计的系数函数的极值
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Estimates non parametrically the extremal coefficient function.
估计非参数系数函数的极值。
用法----------Usage----------
fitextcoeff(data, coord, ..., estim = "ST", marge = "emp", prob = 0,
plot = TRUE, loess = TRUE, method = "BFGS", std.err = TRUE, xlab,
ylab, angles = NULL, identify = FALSE)
参数----------Arguments----------
参数:data
A matrix representing the data. Each column corresponds to one location.
矩阵表示数据。每一列对应于一个位置。
参数:coord
A matrix that gives the coordinates of each location. Each row corresponds to one location.
的矩阵,使每一个位置的坐标。每一行对应于一个位置。
参数:...
Additional options to be passed to the plot function.
到传递给plot功能的附加选项。
参数:estim
Character string specifying the estimator to be used. Must be one of "ST" (Schlather and Tawn) or "Smith".
字符串指定要使用的估计。必须是一个“ST”(Schlather和Tawn)或“史密斯”。
参数:marge
Character string specifying how margins are transformed to unit Frechet. Must be one of "emp", "mle" or "none" - see Details
字符串指定如何将利润转化为单位的Frechet。必须有一个“EMP”,“最大似然估计”或“无” - 查看详细资料
参数:prob
The probability related to the threshold. Only useful with the ST estimator.
相关的阈值的概率。仅ST估计。
参数:plot
Logical. If TRUE (default), the extremal coefficient function is plotted
逻辑。如果TRUE(默认),系数函数的极值绘制
参数:loess
If TRUE (default), a local polynomial curve is plotted - see function loess.
如果TRUE(默认),局部多项式曲线的绘制 - 功能loess。
参数:method
The optimizer used when fitting the GEV distribution to data. See function gevmle.
GEV分布拟合数据时,优化器使用。请参阅功能gevmle。
参数:std.err
Logical. If TRUE, standard errors are computed. Note that standard errors are not available with the "ST" estimator.
逻辑。如果TRUE,标准误差计算。请注意,与“ST”估计标准误差不提供。
参数:xlab,ylab
The x-axis and y-axis labels. May be missing.
x轴和y轴的标签。可能会丢失。
参数:angles
A numeric vector. A partition of the interval (-π, π) to help detecting anisotropy.
一个数值向量。分区的间隔(-π, π)帮助检测各向异性。
参数:identify
Logical. If TRUE, users can use the identify function to identify pairs of stations on the plot.
逻辑。如果TRUE,用户可以使用identify功能,以确定对站上的图。
Details
详细信息----------Details----------
During the estimation procedure, data need to be transformed to unit Frechet margins firts. This can be done in two different ways ; by using the empirical CDF or the GEV ML estimates.
在估计过程中,需要将数据转化为单位的Frechet空间firts。这可以通过两种不同的方式中,通过使用经验CDF或的GEV ML估计。
If marge = "emp", then the data are transformed using the following relation:
如果marge = "emp",然后数据被转换使用下面的关系式:
where y_i are the observations available at location i, F is the empirical CDF and z_i are the observations transformed to unit Frechet scale.
y_i是观测的位置i,F是经验CDF和z_i的意见转化为单位的Frechet规模。
If marge = "mle", then the data are transformed using the MLE of the GEV distribution - see function gev2frech.
如果marge = "mle",然后将数据转化使用的GEV分布的极大似然估计 - 功能gev2frech。
Lastly, if data are already supposed to be unit Frechet, then no transformation is performed if one passed the option marge = "frech".
最后,如果数据已经被认为是单位的导数,则没有转变,如果一个人通过选项marge = "frech"。
If data are already componentwise maxima, prob should be zero. Otherwise, users have to define a threshold z (large enough) where univariate extreme value arguments are relevant. We define prob such that Pr[Z <= z] = prob.
如果data已有的分支的最大值,prob应该是零。否则,用户必须定义的阈值z(足够大),单变量极端值参数相关。我们定义“probPr[Z <= z] = prob。
值----------Value----------
Plots the extremal coefficient function and returns the points used for the plot. If loess = TRUE, the output is a list with argument "ext.coeff" and "loess".
图系数函数的极值和返回点的图。如果loess = TRUE,输出参数“ext.coeff”和“黄土”的列表。
(作者)----------Author(s)----------
Mathieu Ribatet
参考文献----------References----------
multivariate and spatial extreme values: Properties and inference. Biometrika 90(1):139–156.
extremes. Unpublished manuscript.
参见----------See Also----------
madogram
madogram
实例----------Examples----------
n.site <- 30
locations <- matrix(runif(2*n.site, 0, 10), ncol = 2)
colnames(locations) <- c("lon", "lat")
##Simulate a max-stable process - with unit Frechet margins[#模拟一个最大稳定的过程 - 与单位的Frechet空间]
data <- rmaxstab(50, locations, cov.mod = "gauss", cov11 = 10, cov12 =
40, cov22 = 220)
##Plot the extremal coefficient function[#图系数函数的极值]
op <- par(mfrow=c(1,2))
fitextcoeff(data, locations, estim = "Smith")
fitextcoeff(data, locations, angles = seq(-pi, pi, length = 4), estim = "Smith")
par(op)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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