CovSest(rrcov)
CovSest()所属R语言包：rrcov
S Estimates of Multivariate Location and Scatter
多元分布的位置和分散的测算
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes S-Estimates of multivariate location and scatter based on Tukey's biweight function using a fast algorithm similar to the one proposed by Salibian-Barrera and Yohai (2006) for the case of regression. Alternativley, the Ruppert's SURREAL algorithm, bisquare or Rocke type estimation can be used.
计算S-Tukey的biweight功能使用的情况下，回归Salibian巴雷拉和Yohai的（2006）提出的一个类似的快速算法的基础上的多元分布的位置和分散的估计。一种可能的选择，Ruppert公司的超现实的算法，bisquare或Rocke类型估计可以使用。
用法----------Usage----------
CovSest(x, bdp = 0.5, arp = 0.1, eps = 1e-5, maxiter = 120,
nsamp = 500, seed = NULL, trace = FALSE, tolSolve = 1e-14,
method = c("sfast", "surreal", "bisquare", "rocke", "suser"), control,
t0, S0, initcontrol)
参数----------Arguments----------
参数：x
a matrix or data frame.
一个矩阵或数据框。
参数：bdp
a numeric value specifying the required breakdown point. Allowed values are between (n - p)/(2 * n) and 1 and the default is bdp=0.5.
一个数字值，该值指定所需的击穿点。允许值之间(n - p)/(2 * n)1，默认是bdp=0.5。
参数：arp
a numeric value specifying the asympthotic rejection point (for the Rocke type S estimates), i.e. the fraction of points receiving zero weight (see Rocke (1996)). Default is arp=0.1.
一个数值指定的asympthotic的抑制点（对的Rocke型S估计），即权重为零（见Rocke（1996））的点的分数。默认是arp=0.1。
参数：eps
a numeric value specifying the relative precision of the solution of the S-estimate (bisquare and Rocke type). Default is to eps=1e-5.
一个数字值，该值指定的S-估计（bisquare和Rocke类型）的溶液的相对精度。默认值为eps=1e-5。
参数：maxiter
maximum number of iterations allowed in the computation of the S-estimate (bisquare and Rocke type). Default is maxiter=120.
计算的S-估计（bisquare和Rocke类型）中允许的迭代的最大数量。默认是maxiter=120。
参数：nsamp
the number of random subsets considered. The default is different for the different methods: (i) for sfast it is nsamp = 20, (ii) for surreal it is nsamp = 600*p and (iii) for bisquare or rocke it is nsamp = 500.
考虑的随机子集的数量。默认值是不同的不同的方法：（i）为sfast是nsamp = 20，（ii）为surreal是nsamp = 600*p及（iii）为<X >或bisquare是rocke。
参数：seed
starting value for random generator. Default is seed = NULL.
随机数发生器的初始值。默认是seed = NULL。
参数：trace
whether to print intermediate results. Default is trace = FALSE.
是否要打印的中间结果。默认是trace = FALSE。
参数：tolSolve
numeric tolerance to be used for inversion (solve) of the covariance matrix in mahalanobis.
数字耐受用于反转（solve）的协方差矩阵在mahalanobis。
参数：method
Which algorithm to use: 'sfast'=C implementation of FAST-S, 'surreal'=SURREAL, 'bisquare', 'rocke'. The method 'suser' currently calls the R implementation of FAST-S but in the future will allow the user to supply own rho function.
要使用的算法：“sfast= C实现的FAST-S，超现实=贺岁片，”bisquare“，”rocke“。目前的suser的方法调用的R实现的FAST-S，但在未来将允许用户提供自己的rho函数。
参数：control
a control object (S4) of class CovControlSest-class containing estimation options - same as these provided in the fucntion 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.
控制对象（S4）类CovControlSest-class估计选项 - 因为这些在温控功能规格提供相同。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。
参数：t0
optional initial HBDP estimate for the center
可选的初始HBDP的估计为中心
参数：S0
optional initial HBDP estimate for the covariance matrix
可选的的初始HBDP估计的协方差矩阵
参数：initcontrol
optional control object to be used for computing the initial HBDP estimates
用于计算初始HBDP估计的可选的控制对象物的
Details
详细信息----------Details----------
Computes multivariate S-estimator of location and scatter. The computation will be performed by one of the following algorithms:
计算位置和分散的多元S-估计。将被执行的计算由下列算法之一：
FAST-S An algorithm similar to the one proposed by Salibian-Barrera and Yohai (2006) for the case of regression
FAST-S回归的情况下，Salibian巴雷拉和Yohai的（2006）提出的一个类似的算法
SURREAL Ruppert's SURREAL algorithm when method is set to 'surreal'
超现实主义的鲁珀特的超现实主义的算法时method设置为“超现实主义”
BISQUARE Bisquare S-Estimate with method set to 'bisquare'
BISQUARE Bisquare估计用S-method设置bisquare的“
ROCKE Rocke type S-Estimate with method set to 'rocke'
ROCKE Rocke用S型估计method设置为“rocke的”
Except for the last algorithm, ROCKE, all other use Tukey biweight loss function. The tuning parameters used in the loss function (as determined by bdp) are returned in the slots cc and kp of the result object. They can be computed by the internal function rrcov:::.csolve.bw.S(bdp, p).
除最后的算法，ROCKE，所有其他用途杜克biweight损失函数。调整（BDP）的损失函数中使用的参数中返回的插槽cc和kp结果对象。它们可以计算由内部函数rrcov:::.csolve.bw.S(bdp, p)。
值----------Value----------
An S4 object of class CovSest-class which is a subclass of the virtual class CovRobust-class.
S4对象的类CovSest-class这是虚拟类CovRobust-class的一个子类。
（作者）----------Author(s)----------
Valentin Todorov <a href="mailto:valentin.todorov@chello.at">valentin.todorov@chello.at</a>,
Matias Salibian-Barrera <a href="mailto:matias@stat.ubc.ca">matias@stat.ubc.ca</a> and
Victor Yohai <a href="mailto:vyohai@dm.uba.ar">vyohai@dm.uba.ar</a>. See also the code from
Kristel Joossens, K.U. Leuven, Belgium and Ella Roelant, Ghent University, Belgium.
参考文献----------References----------
Multivariate Location and Covariance. Annals of Statistics 17 1662–1683.
Location/Dispersion. Journal of Computational and Graphical Statistics 1 253–270.
estimates, Journal of Computational and Graphical Statistics, 15, 414–427.
Wiley, New York.
An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
实例----------Examples----------
library(rrcov)
data(hbk)
hbk.x <- data.matrix(hbk[, 1:3])
CovSest(hbk.x)
## the following four statements are equivalent[＃以下四个语句是等价的]
c0 <- CovSest(hbk.x)
c1 <- CovSest(hbk.x, bdp = 0.25)
c2 <- CovSest(hbk.x, control = CovControlSest(bdp = 0.25))
c3 <- CovSest(hbk.x, control = new("CovControlSest", bdp = 0.25))
## direct specification overrides control one:[＃直接指定覆盖控制1：]
c4 <- CovSest(hbk.x, bdp = 0.40,
control = CovControlSest(bdp = 0.25))
c1
summary(c1)
plot(c1)
## Use the SURREAL algorithm of Ruppert[＃使用的超现实主义的算法鲁珀特]
cr <- CovSest(hbk.x, method="surreal")
cr
## Use Bisquare estimation[＃使用Bisquare估计]
cr <- CovSest(hbk.x, method="bisquare")
cr
## Use Rocke type estimation[＃使用Rocke型估计]
cr <- CovSest(hbk.x, method="rocke")
cr
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注：
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发表于 2012-9-28 20:45:52
