covMest(rrcov)
covMest()所属R语言包：rrcov
Constrained M-Estimates of Location and Scatter
约束M-估计的位置与散布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes constrained M-Estimates of multivariate location and scatter based on the translated biweight function ("t-biweight") using a High breakdown point initial estimate. The default initial estimate is the Minimum Volume Ellipsoid computed with CovMve. The raw (not reweighted) estimates are taken and the covariance matrix is standardized to determinant 1.
计算约束的M-估计的多变量的位置和分散的基础上翻译biweight功能（T-biweight）使用高击穿点初步估计。默认的初始估计是最小体积椭球计算CovMve。原（不重加权）估计和协方差矩阵是标准化的行列式为1。
用法----------Usage----------
covMest(x, cor=FALSE, r = 0.45, arp = 0.05, eps=1e-3,
maxiter=120, control, t0, S0)
参数----------Arguments----------
参数：x
a matrix or data frame.
一个矩阵或数据框。
参数：cor
should the returned result include a correlation matrix? Default is cor = FALSE </table>
返回的结果应包括相关矩阵？默认是cor = FALSE</ TABLE>
参数：r
required breakdown point. Allowed values are between (n - p)/(2 * n) and 1 and the default is 0.45
需要故障点。允许值之间(n - p)/(2 * n)1，默认是0.45
参数：arp
asympthotic rejection point, i.e. the fraction of points receiving zero weight (see Rocke (1996)). Default is 0.05.
asympthotic抑制点，即接收零重量（见Rocke（1996年））的点的馏分。默认是0.05。
参数：eps
a numeric value specifying the relative precision of the solution of the M-estimate. Defaults to 1e-3
一个数字值，该值指定的M-估计的溶液的相对精确性。默认为1e-3
参数：maxiter
maximum number of iterations allowed in the computation of the M-estimate. Defaults to 120
的M-估计在计算允许的最大数目的迭代。默认为120
参数：control
a list with 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.
估计选项 - 因为这些在温控功能规格提供相同的列表。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 high breakdown point estimates of the location. If not supplied MVE will be used.
可选的初始破裂点的位置估计。如果未提供MVE将被使用。
参数：S0
optional initial high breakdown point estimates of the scatter. If not supplied MVE will be used.
可选的初始破裂点估计的散射。如果未提供MVE将被使用。
Details
详细信息----------Details----------
Rocke (1996) has shown that the S-estimates of multivariate location and scatter in high dimensions can be sensitive to outliers even if the breakdown point is set to be near 0.5. To mitigate this problem he proposed to utilize the translated biweight (or t-biweight) method with a standardization step consisting of equating the median of rho(d) with the median under normality. This is then not an S-estimate, but is instead a constrained M-estimate. In order to make the smooth estimators to work, a reasonable starting point is necessary, which will lead reliably to a good solution of the estimator. In covMest the MVE computed by CovMve is used, but the user has the possibility to give her own initial estimates.
Rocke（1996）表明，在高维空间中的位置和分散多元的S-估计是敏感的对孤立点的，即使故障点被设置为接近0.5。为了缓解这一问题，他建议利用翻译biweight（或T-biweight的）方法的标准化步骤，包括等同的中位数rho(d)与常态下的中位数。这是不是一个S-估计，但却是一种约束的M-估计。为了使工作顺利的估计，合理的出发点是必要的，这将导致一个很好的解决方案，可靠地估计。在covMestCovMve MVE计算使用，但用户有可能给自己的初步估计。
值----------Value----------
An object of class "mest" which is basically a list with the following components. This class is "derived" from "mcd" so that the same generic functions - print, plot, summary - can be used. NOTE: this is going to change - in one of the next revisions covMest will return an S4 class "mest" which is derived (i.e. contains) form class "cov".
对象的类"mest"这基本上是一个list有以下组件。这个类是“导出”从"mcd"“这样相同的通用功能 - print，plot，summary - 可以使用。注意：这是怎么回事改变 - 在一个未来的修订covMest将返回S4类"mest"衍生（即contains）窗体类"cov"。
参数：center
the final estimate of location.
最终的位置估计。
参数：cov
the final estimate of scatter.
分散的最终估计。
参数：cor
the estimate of the correlation matrix (only if cor = TRUE).
估计的相关矩阵（只有cor = TRUE“）。
参数：mah
mahalanobis distances of the observations using the M-estimate of the location and scatter.
使用M-估计的位置和散射的观测的马哈拉诺比斯距离。
参数：X
the input data as a matrix.
的输入数据作为一个矩阵。
参数：n.obs
total number of observations.
观察的总数。
参数：method
character string naming the method (M-Estimates).
字符串命名的方法（M-估计）。
参数：call
the call used (see match.call).
使用的呼叫（见match.call“）。
注意----------Note----------
The psi, rho and weight functions for the M estimation are encapsulated in a virtual S4 class PsiFun from which a PsiBwt class, implementing the translated biweight (t-biweight), is dervied. The base class PsiFun contains also the M-iteration itself. Although not documented and not accessibale directly by the user these classes will form the bases for adding other functions (biweight, LWS, etc.) as well as S-estimates.
磅，rho和权重函数M估计封装在一个虚拟S4类PsiFunPsiBwt类，执行翻译biweight（叔biweight），dervied中。基类PsiFun也包含M-迭代本身。虽然未记录，而不是由用户直接accessibale这些类将形成用于添加其他功能（biweight，LWS，等。）以及S-估计的基础。
（作者）----------Author(s)----------
Valentin Todorov <a href="mailto:valentin.todorov@chello.at">valentin.todorov@chello.at</a>,
(some code from C. Becker -
http://www.sfb475.uni-dortmund.de/dienst/de/content/struk-d/bereicha-d/tpa1softw-d.html)
参考文献----------References----------
and shape on high dimension using compound estimators, Journal of the American Statistical Association, 89, 888–896.
shape in high dimension, Annals of Statistics, 24, 1327-1345.
of the American Statistical Association, 91, 1047–1061.
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
covMcd
实例----------Examples----------
data(hbk)
hbk.x <- data.matrix(hbk[, 1:3])
covMest(hbk.x)
## the following three statements are equivalent[＃以下三个语句是等价的]
c0 <- covMest(hbk.x)
c1 <- covMest(hbk.x, r = 0.45)
c2 <- covMest(hbk.x, control = rrcov.control(r = 0.45))
## direct specification overrides control one:[＃直接指定覆盖控制1：]
c3 <- covMest(hbk.x, r = 0.45,
control = rrcov.control(r=0.25))
c1
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。
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发表于 2012-9-28 20:44:09
