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

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

                                         Generic Function for the Computation of the Optimal Clipping Bound
                                         通用功能的最优裁剪绑定的计算

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Generic function for the computation of the optimal clipping bound. This function is rarely called directly. It is called by getInfClipRegTS  to compute optimally robust ICs.
通用函数的计算绑定的最佳剪辑。很少直接调用此函数。这就是所谓的getInfClipRegTS的来计算最佳强大的IC。


用法----------Usage----------


getInfGammaRegTS(ErrorL2deriv, Regressor, risk, neighbor, ...)

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

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

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

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

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

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

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

## S4 method for signature 'RealRandVariable,Distribution,asMSE,ContNeighborhood'
getInfGammaRegTS(ErrorL2deriv,
                Regressor, risk, neighbor, ErrorDistr, stand, cent, clip)

## S4 method for signature 'RealRandVariable,Distribution,asMSE,Av1CondContNeighborhood'
getInfGammaRegTS(ErrorL2deriv,
                Regressor, risk, neighbor, ErrorDistr, stand, cent, clip)

## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asUnOvShoot,ContNeighborhood'
getInfGammaRegTS(ErrorL2deriv,
                Regressor, risk, neighbor, cent, clip)

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

## S4 method for signature 'UnivariateDistribution,numeric,asUnOvShoot,CondContNeighborhood'
getInfGammaRegTS(ErrorL2deriv,
                Regressor, risk, neighbor, clip)

## S4 method for signature 'UnivariateDistribution,numeric,asUnOvShoot,CondTotalVarNeighborhood'
getInfGammaRegTS(ErrorL2deriv,
                Regressor, risk, neighbor, clip)



参数----------Arguments----------

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


参数：Regressor
regressor.
回归量。


参数：risk
object of class "RiskType".
对象类"RiskType"。


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


参数：...
additional parameters.
附加参数。


参数：clip
optimal clipping bound.
最佳剪裁的约束。


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：ErrorDistr
error distribution.
误差分布。


Details

详细信息----------Details----------

The function is used in case of asymptotic G-risks; confer Ruckdeschel and Rieder (2004).
渐近G-风险;赋予Ruckdeschel和里德尔（2004年）的情况下，在使用该功能。


方法----------Methods----------

  


ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "ContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asMSE”的，邻居=的“ContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asMSE”的，邻居=的“Av1CondContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "Av1CondTotalVarNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asMSE”的，邻居=的“Av1CondTotalVarNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "ContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=“asMSE”的，邻居=的“ContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=“asMSE”的，邻居=的“Av1CondContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "Av1CondTotalVarNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=“asMSE”的，邻居=的“Av1CondTotalVarNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asMSE", neighbor = "Av2CondContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“风险分配”，=“asMSE”的，邻居=的“Av2CondContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asMSE", neighbor = "ContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，的风险=“asMSE”的，邻居=的“ContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，的风险=“asMSE”的，邻居=的“Av1CondContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "ContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asUnOvShoot”的，邻居=的“ContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "TotalVarNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asUnOvShoot”的，邻居=的“TotalVarNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "numeric", risk = "asUnOvShoot", neighbor = "CondContNeighborhood"  used by getInfClipRegTS.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“数字”，风险的“asUnOvShoot”，邻居=的“CondContNeighborhood”使用getInfClipRegTS。




ErrorL2deriv = "UnivariateDistribution", Regressor = "numeric", risk = "asUnOvShoot", neighbor = "CondTotalVarNeighborhood"  used by getInfClipRegTS.   
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“数字”，风险的“asUnOvShoot”，邻居=的“CondTotalVarNeighborhood”使用getInfClipRegTS。


（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.
Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for General Loss Functions. Statistics &amp; Decisions (submitted).
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness.  Bayreuth: Dissertation.

参见----------See Also----------

asMSE-class, asUnOvShoot-class,  ContIC-class, Av1CondContIC-class,  Av2CondContIC-class, Av1CondTotalVarIC-class,
asMSE-class，asUnOvShoot-class，ContIC-class，Av1CondContIC-class，Av2CondContIC-class，Av1CondTotalVarIC-class，

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