covRob(robust)
covRob()所属R语言包：robust
Robust Covariance/Correlation Matrix Estimation
强大的协方差/相关矩阵估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute robust estimates of multivariate location and scatter.
计算多元的位置和分散可靠的估计数。
用法----------Usage----------
covRob(data, corr = FALSE, distance = TRUE, na.action = na.fail,
estim = "auto", control = covRob.control(estim, ...), ...)
参数----------Arguments----------
参数：data
a numeric matrix or data frame containing the data.
数值矩阵或包含数据的数据框。
参数：corr
a logical flag. If corr = TRUE then the estimated correlation matrix is computed.
一个逻辑标志。如果corr = TRUE然后估计的相关矩阵计算。
参数：distance
a logical flag. If distance = TRUE the squared Mahalanobis distances are computed.
一个逻辑标志。如果distance = TRUE的平方马氏距离计算。
参数：na.action
a function to filter missing data. The default na.fail produces an error if missing values are present. An alternative is na.omit which deletes observations that contain one or more missing values.
一个函数来筛选丢失的数据。默认na.fail产生一个错误，如果存在遗漏值。另一种方法是na.omit删除包含一个或多个缺失值的观察。
参数：estim
a character string specifying the robust estimator to be used. The choices are: "mcd" for the Fast MCD algorithm of Rousseeuw and Van Driessen, "weighted" for the Reweighted MCD, "donostah" for the Donoho-Stahel projection based estimator, "M" for the constrained M estimator provided by Rocke, "pairwiseQC" for the orthogonalized quadrant correlation pairwise estimator, and "pairwiseGK" for the Orthogonalized Gnanadesikan-Kettenring pairwise estimator. The default "auto" selects from "donostah", "mcd", and "pairwiseQC" with the goal of producing a good estimate in a reasonable amount of time.
一个字符串，指定要使用的鲁棒估计。的选择是：“MCD”Driessen的Rousseeuw和Van快速MCD算法，的重加权MCD的“加权”，Donoho提出的基于Stahel投影估计的的“donostah”，“M”的约束M估计Rocke，成对估计的正交象限相关的“pairwiseQC”，和的“pairwiseGK”为的正交化格纳纳德西肯 - Kettenring的成对的估计。默认的“自动”选择“donostah”，“MCD”，“pairwiseQC”的目标在一个合理的时间内产生了良好的估计。
参数：control
a list of control parameters to be used in the numerical algorithms. See covRob.control for the possible control parameters and their default settings. This argument is ignored when estim = "auto".
要使用的控制参数的列表中的数值算法。 covRob.control可能的控制参数及其默认设置。时，此参数将被忽略estim = "auto"。
参数：...
control parameters may be passed directly when estim != "auto".
控制参数时，可能会通过直接estim != "auto"。
Details
详细信息----------Details----------
The covRob function selects a robust covariance estimator that is likely to provide a good estimate in a reasonable amount of time. Presently this selection is based on the problem size. The Donoho-Stahel estimator is used if there are less than 1000 observations and less than 10 variables or less than 5000 observations and less than 5 variables. If there are less than 50000 observations and less than 20 variables then the MCD is used. For larger problems, the Orthogonalized Quadrant Correlation estimator is used.
covRob功能选择一个强大的协方差估计，很可能在一个合理的时间内提供一个很好的估计。目前，这个选择是根据问题的大小。 Donoho提出Stahel估计器使用，如果有小于1000意见和少于10个变量或小于5000观测和少于5个变量。如果有小于50000的观测和小于20个变量，那么使用的MCD。对于较大的问题，正交化象限相关估计。
The MCD and Reweighted-MCD estimates (estim = "mcd" and estim = "weighted" respectively) are computed using the covMcd function in the robustbase package. By default, covMcd returns the reweighted estimate; the actual MCD estimate is contained in the components of the output list prefixed with raw.
的MCD和重加权MCD估计（estim = "mcd"和estim = "weighted"分别）计算covMcd功能，在robustbase包。默认情况下，covMcd返回的再加权估计的实际MCD估计包含在输出列表前缀raw的组成部分。
The M estimate (estim = "M") is computed using the covMest function in the rrcov package. For historical reasons the Robust Library uses the MCD to compute the initial estimate.
的M估计（estim = "M"）的计算使用covMest功能的在rrcov包。由于历史的原因，强大的库使用MCD计算的初步估计。
The Donoho-Stahel (estim = "donostah") estimator is computed using the CovSde function provided in the rrcov package.
Donoho提出Stahel（estim = "donostah"）估计计算使用CovSde功能在rrcov包。
The pairwise estimators (estim = "pairwisegk" and estim = "pairwiseqc") are computed using the CovOgk function in the rrcov package.
两两估计（estim = "pairwisegk"和estim = "pairwiseqc"）是使用CovOgk函数计算在rrcov包。
值----------Value----------
an object of class "covRob" with components:
类的一个对象“covRob”的组成部分：
参数：call
an image of the call that produced the object with all the arguments named.
的呼叫，产生与所有的参数命名的对象的图像。
参数：cov
a numeric matrix containing the final robust estimate of the covariance/correlation matrix.
含有最终的鲁棒估计的协方差/相关矩阵的数字矩阵。
参数：center
a numeric vector containing the final robust estimate of the location vector.
含有最终的鲁棒估计的位置矢量的一个数值向量。
参数：dist
a numeric vector containing the squared Mahalanobis distances computed using robust estimates of covariance and location contained in cov and center. If distance = FALSE this element is set to NA.
一个数值向量的平方马氏距离使用在cov和center协方差和位置的可靠的估计数计算。如果distance = FALSE这个元素是设置为NA。
参数：raw.cov
a numeric matrix containing the initial robust estimate of the covariance/correlation matrix. If there is no initial robust estimate then this element is set to NA.
一个包含初始稳健估计的协方差/相关矩阵的数值矩阵。如果没有最初的稳健估计，那么这个元素被设置为NA。
参数：raw.center
a numeric vector containing the initial robust estimate of the location vector. If there is no initial robust estimate then this element is set to NA.
一个数值向量含有的初始的位置矢量的鲁棒估计。如果没有最初的稳健估计，那么这个元素被设置为NA。
参数：raw.dist
a numeric vector containing the squared Mahalanobis distances computed using the initial robust estimates of covariance and location contained in raw.cov and raw.center. If distance = FALSE or if there is no initial robust estimate then this element is set to NA.
一个数字的平方马氏距离计算的初始地估计协方差和位置在raw.cov和raw.center向量。如果distance = FALSE如果没有最初的稳健估计，则此元素的设置为NA。
参数：corr
a logical flag. If corr = TRUE then cov and raw.cov contain robust estimates of the correlation matrix of data.
一个逻辑标志。如果corr = TRUE然后cov和raw.cov包含可靠的估计数的相关系数矩阵的data。
参数：estim
a character string containing the name of the robust estimator.
一个字符串，其中包含的名称鲁棒估计。
参数：control
a list containing the control parameters used by the robust estimator.
一个列表，其中包含控制参数的鲁棒估计。
注意----------Note----------
Version 0.3-8 of the Robust Library: all of the functions origianlly contributed by the S-Plus Robust Library have been replaced by dependencies on the robustbase and rrcov packages. Computed results may differ from earlier versions of the Robust Library. In particular, the MCD estimators are now adjusted by a small sample size correction factor. Additionally, a bug was fixed where the final MCD covariance estimate produced with estim = "mcd" was not rescaled for consistency.
已被取代的robustbase和rrcov包依赖于版本0.3-8的鲁棒图书馆：的功能origianlly都提供S-PLUS强大的图书馆。计算结果可能会有所不同，从早期版本的鲁棒图书馆。特别是，正在由一个小的样本尺寸校正因子调整的MCD估计。此外，错误是固定的地方，最后MCD协方差估计生产estim = "mcd"不重新调整的一致性。
参考文献----------References----------
参见----------See Also----------
CovSde, covMcd, CovOgk, covMest, covRob.control, ccov.
CovSde，covMcd，CovOgk，covMest，covRob.control，ccov。
实例----------Examples----------
data(stackloss)
covRob(stackloss)
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。
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发表于 2012-9-27 22:30:25
