R语言 ROptRegTS包 getInfStandRegTS()函数中文帮助文档(中英文对照)

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getInfStandRegTS(ROptRegTS)
getInfStandRegTS()所属R语言包：ROptRegTS

                                         Generic Function for the Computation of the Standardizing Matrix
                                         为规范化矩阵计算的通用功能

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Generic function for the computation of the standardizing matrix which takes care of the Fisher consistency of the corresponding IC. This function  is rarely called directly. It is used to compute optimally robust ICs.
通用功能的标准化矩阵计算相应的IC费雪一致性负责。很少直接调用此函数。它被用来计算最佳鲁棒的IC。


用法----------Usage----------


getInfStandRegTS(ErrorL2deriv, Regressor, neighbor, ...)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,ContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,TotalVarNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, clip, cent)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,CondTotalVarNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, clip, cent)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,Av1CondContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,Av1CondTotalVarNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,ContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,Av1CondContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,Av1CondTotalVarNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'UnivariateDistribution,Distribution,Av2CondContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, z.comp, clip, cent, stand, trafo)

## S4 method for signature 'RealRandVariable,Distribution,ContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, ErrorDistr, A.comp, stand, clip, cent, trafo)

## S4 method for signature 'RealRandVariable,Distribution,Av1CondContNeighborhood'
getInfStandRegTS(ErrorL2deriv,
                Regressor, neighbor, ErrorDistr, A.comp, stand, clip, cent, trafo)



参数----------Arguments----------

参数：ErrorL2deriv
L2-derivative of ErrorDistr.
L2衍生ErrorDistr。


参数：Regressor
regressor.
回归量。


参数：neighbor
object of class "Neighborhood".
对象类"Neighborhood"。


参数：...
additional parameters.
附加参数。


参数：ErrorDistr
error distribution.
误差分布。


参数：clip
optimal clipping bound/function.
最佳削波/函数绑定。


参数：cent
optimal centering constant/function.
最佳定心常数/功能。


参数：stand
standardizing matrix.
规范矩阵。


参数：z.comp
which components of the centering constant/function  have to be computed.
定心的常数/功能的组成部分有以被计算。


参数：A.comp
which components of the standardizing matrix have to be computed.
组件标准化矩阵以计算。


参数：trafo
matrix: transformation of the parameter.
矩阵变换的参数。


值----------Value----------

The standardizing matrix is computed.
的标准化矩阵计算。


方法----------Methods----------

  


ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "ContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“UnivariateDistribution”，邻居=“ContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"  computes standardizing constant.
ErrorL2deriv =“UnivariateDistribution”的，REGRESSOR =的“UnivariateDistribution”邻居=“TotalVarNeighborhood”的计算规范不变。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "CondTotalVarNeighborhood"  computes standardizing constant.
ErrorL2deriv =“UnivariateDistribution”的，REGRESSOR =的“UnivariateDistribution”邻居=“CondTotalVarNeighborhood”的计算规范不变。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "Av1CondContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“UnivariateDistribution”，邻居=“Av1CondContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "Av1CondTotalVarNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“UnivariateDistribution”，邻居=“Av1CondTotalVarNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "ContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“MultivariateDistribution”，邻居=“ContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "Av1CondContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“MultivariateDistribution”，邻居=“Av1CondContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "Av1CondTotalVarNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =的“MultivariateDistribution”，邻居=“Av1CondTotalVarNeighborhood”计算标准化矩阵。




ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", neighbor = "Av2CondContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，邻居=“Av2CondContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", neighbor = "ContNeighborhood"  computes standardizing matrix.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，邻居=“ContNeighborhood”计算标准化矩阵。




ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", neighbor = "Av1CondContNeighborhood"  computes standardizing matrix.   
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，邻居=“Av1CondContNeighborhood”计算标准化矩阵。


（作者）----------Author(s)----------


Matthias Kohl <a href="mailto:Matthias.Kohl@stamats.de">Matthias.Kohl@stamats.de</a>



参考文献----------References----------

Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. 8: 106&ndash;115.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness.  Bayreuth: Dissertation.

参见----------See Also----------

ContIC-class, TotalVarIC-class,  Av1CondContIC-class, Av2CondContIC-class,  Av1CondTotalVarIC-class, CondContIC,
ContIC-class，TotalVarIC-class，Av1CondContIC-class，Av2CondContIC-class，Av1CondTotalVarIC-class，CondContIC，

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