CovOgk(rrcov)
CovOgk()所属R语言包：rrcov
Robust Location and Scatter Estimation - Ortogonalized Gnanadesikan-Kettenring (OGK)
强大的位置与散布估计 - Ortogonalized的格纳纳德西肯 - Kettenring（OGK）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes a robust multivariate location and scatter estimate with a high breakdown point, using the pairwise algorithm proposed by Marona and Zamar (2002) which in turn is based on the pairwise robust estimator proposed by Gnanadesikan-Kettenring (1972).
计算稳健多变量的位置和散射估计具有高的击穿点，使用成对的算法由Marona和Zamar（2002），而这又是基于由格纳纳德西肯Kettenring（1972）提出的成对的鲁棒估计。
用法----------Usage----------
CovOgk(x, niter = 2, beta = 0.9, control)
参数----------Arguments----------
参数：x
a matrix or data frame.
一个矩阵或数据框。
参数：niter
number of iterations, usually 1 or 2 since iterations beyond the second do not lead to improvement.
次数的迭代，通常为1或2，因为超出第二迭代不导致改善。
参数：beta
coverage parameter for the final reweighted estimate
最终重新加权估计的覆盖参数
参数：control
a control object (S4) of class CovControlOgk-class containing estimation options - same as these provided in the function specification. If the control object is supplied, the parameters from it will be used. If parameters are passed also in the invocation statement, they will override the corresponding elements of the control object. The control object contains also functions for computing the robust univariate location and dispersion estimate mrob and for computing the robust estimate of the covariance between two random variables vrob.
控制对象（S4）类CovControlOgk-class估计选项 - 这些在功能规格相同。如果被供给的控制对象，从它的参数将被使用。如果参数传递的调用语句，它们将覆盖相应元素的控制对象。控制对象包含也功能计算出强大的单变量的位置和分散估计mrob和计算之间的协方差的稳健估计的两个随机变量vrob。
Details
详细信息----------Details----------
The method proposed by Marona and Zamar (2002) allowes to obtain positive-definite and almost affine equivariant robust scatter matrices starting from any pairwise robust scatter matrix. The default robust estimate of covariance between two random vectors used is the one proposed by Gnanadesikan and Kettenring (1972) but the user can choose any other method by redefining the function in slot vrob of the control object CovControlOgk. Similarly, the function for computing the robust univariate location and dispersion used is the tau scale defined in Yohai and Zamar (1998) but it can be redefined in the control object.
的Marona和Zamar（2002）提出的方法，让您可以得到正定，几乎仿射等变强大的散射矩阵从任何成对强大的散射矩阵。默认的稳健估计的两个随机向量之间的协方差是一个格纳纳德西肯和Kettenring（1972）提出的，但通过重新定义的功能插槽中vrobCovControlOgk的控制对象，用户可以选择任何其他的方法 。同样地，该函数用于计算鲁棒单变量的位置和分散体，用于tau scale在Yohai和Zamar（1998）定义的，但它可以在控制对象重新定义。
The estimates obtained by the OGK method, similarly as in CovMcd are returned as 'raw' estimates. To improve the estimates a reweighting step is performed using the coverage parameter beta and these reweighted estimates are returned as 'final' estimates.
的的OGK方法，同样作为CovMcd返回的是“原始”估计得到的估计数字。为了提高估计一个权重调整的步骤是使用覆盖参数beta和这些再加权估计返回的是最后估计。
值----------Value----------
An S4 object of class CovOgk-class which is a subclass of the virtual class CovRobust-class.
S4对象的类CovOgk-class这是虚拟类CovRobust-class的一个子类。
注意----------Note----------
If the user does not specify a scale and covariance function to be used in the computations or specifies one by using the arguments smrob and svrob (i.e. the names of the functions as strings), a native code written in C will be called which is by far faster than the R version.
如果用户没有指定的规模和协方差函数在计算中使用，或指定一个smrob和svrob（即作为字符串的函数的名称），本机代码编写的，使用的参数在C将被称为是远远快于R版本。
If the arguments mrob and vrob are not NULL, the specified functions will be used via the pure R implementation of the algorithm. This could be quite slow.
如果参数mrob和vrob不是NULL，指定的功能将通过使用纯R的算法实现。这可能是相当缓慢的。
See CovControlOgk for details.
见CovControlOgk的详细信息。
（作者）----------Author(s)----------
Valentin Todorov <a href="mailto:valentin.todorov@chello.at">valentin.todorov@chello.at</a> and
Kjell Konis <a href="mailto:kjell.konis@epfl.ch">kjell.konis@epfl.ch</a>
参考文献----------References----------
Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307–317.
High breakdown point estimates of regression by means of the minimization of efficient scale JASA 86, 403–413.
Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics 28, 81–124.
An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
参见----------See Also----------
CovMcd, CovMest
CovMcd，CovMest
实例----------Examples----------
data(hbk)
hbk.x <- data.matrix(hbk[, 1:3])
CovOgk(hbk.x)
## the following three statements are equivalent[＃以下三个语句是等价的]
c1 <- CovOgk(hbk.x, niter=1)
c2 <- CovOgk(hbk.x, control = CovControlOgk(niter=1))
## direct specification overrides control one:[＃直接指定覆盖控制1：]
c3 <- CovOgk(hbk.x, beta=0.95,
control = CovControlOgk(beta=0.99))
c1
x<-matrix(c(1,2,3,7,1,2,3,7), ncol=2)
## CovOgk(x) - this would fail because the two columns of x are exactly collinear.[＃CovOgk（X） - 这将失败，因为两列的x是完全共线。]
## In order to fix it, redefine the default 'vrob' function for example[＃为了解决这个问题，，重新定义的默认“vrob”功能，例如]
## in the following way and pass it as a parameter in the control[＃通过以下方式，并把它作为一个参数控制]
## object.[＃对象。]
cc <- CovOgk(x, control=new("CovControlOgk",
vrob=function(x1, x2, ...)
{
r <- rrcov:::.vrobGK(x1, x2, ...)
if(is.na(r))
r <- 0
r
})
)
cc
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。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-9-28 20:45:03
