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

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getInfGamma(ROptEst)
getInfGamma()所属R语言包：ROptEst

                                        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 getInfClip  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getInfClip的来计算最佳强大的IC。


用法----------Usage----------


getInfGamma(L2deriv, risk, neighbor, biastype, ...)

## S4 method for signature 'UnivariateDistribution,asGRisk,ContNeighborhood,BiasType'
getInfGamma(L2deriv,
     risk, neighbor, biastype, cent, clip)

## S4 method for signature 'UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType'
getInfGamma(L2deriv,
     risk, neighbor, biastype, cent, clip)

## S4 method for signature 'RealRandVariable,asMSE,ContNeighborhood,BiasType'
getInfGamma(L2deriv,
     risk, neighbor, biastype, Distr, stand, cent, clip, power = 1L)

## S4 method for signature 'RealRandVariable,asMSE,TotalVarNeighborhood,BiasType'
getInfGamma(L2deriv,
     risk, neighbor, biastype, Distr, stand, cent, clip, power = 1L)

## S4 method for signature 'UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType'
getInfGamma(L2deriv,
     risk, neighbor, biastype, cent, clip)

## S4 method for signature 'UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias'
getInfGamma(L2deriv,
     risk, neighbor, biastype, cent, clip)

## S4 method for signature 'UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias'
getInfGamma(L2deriv,
    risk, neighbor, biastype, cent, clip)



参数----------Arguments----------

参数：L2deriv
L2-derivative of some L2-differentiable family  of probability measures.
L2-衍生的一些L2-微家庭的概率措施。


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


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


参数：biastype
object of class "BiasType"
对象的类"BiasType"


参数：...
additional parameters
额外的参数


参数：cent
optimal centering constant.
最优的中心不变。


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


参数：stand
standardizing matrix.
规范矩阵。


参数：Distr
object of class "Distribution".
对象类"Distribution"。


参数：power
exponent for the integrand; by default 1, but may also be 2, for optimization in getLagrangeMultByOptim.
指数的积，默认情况下，1，但也可能是2，优化getLagrangeMultByOptim。


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----------

  


L2deriv = "UnivariateDistribution", risk = "asGRisk",  neighbor = "ContNeighborhood",  biastype = "BiasType" used by getInfClip for symmetric bias.
L2deriv =的“UnivariateDistribution”风险=“asGRisk”的，邻居=“ContNeighborhood”，biastype =“BiasType”的使用getInfClip对称偏置。




L2deriv = "UnivariateDistribution", risk = "asGRisk",  neighbor = "TotalVarNeighborhood",  biastype = "BiasType" used by getInfClip for symmetric bias.
L2deriv =的“UnivariateDistribution”风险=“asGRisk”的，邻居=“TotalVarNeighborhood”，biastype =“BiasType”的使用getInfClip对称偏置。




L2deriv = "RealRandVariable", risk = "asMSE",  neighbor = "ContNeighborhood",  biastype = "BiasType" used by getInfClip for symmetric bias.
L2deriv =“RealRandVariable的”风险=“asMSE”的，邻居=“ContNeighborhood”，biastype =“BiasType”的使用getInfClip对称偏置。




L2deriv = "RealRandVariable", risk = "asMSE", neighbor = "TotalVarNeighborhood", biastype = "BiasType" used by getInfClip for symmetric bias.
L2deriv =“RealRandVariable的”风险=“asMSE”的，邻居=“TotalVarNeighborhood”，biastype =“BiasType”的使用getInfClip对称偏置。




L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",  neighbor = "ContNeighborhood",  biastype = "BiasType" used by getInfClip for symmetric bias.
L2deriv =的“UnivariateDistribution”，风险的“asUnOvShoot”，邻居=“ContNeighborhood”，biastype =“BiasType”的使用getInfClip对称偏置。




L2deriv = "UnivariateDistribution", risk = "asMSE",  neighbor = "ContNeighborhood",  biastype = "onesidedBias" used by getInfClip for onesided bias.
L2deriv =的“UnivariateDistribution”风险=“asMSE”的，邻居=“ContNeighborhood”，biastype =“onesidedBias”的使用getInfClip片面的偏见。




L2deriv = "UnivariateDistribution", risk = "asMSE",  neighbor = "ContNeighborhood",  biastype = "asymmetricBias" used by getInfClip for asymmetric bias.   
L2deriv =的“UnivariateDistribution”风险=“asMSE”的，邻居=“ContNeighborhood”，biastype =“asymmetricBias”的使用getInfClip不对称的偏差。


（作者）----------Author(s)----------


Matthias Kohl <a href="mailto:Matthias.Kohl@stamats.de">Matthias.Kohl@stamats.de</a>,
Peter Ruckdeschel <a href="mailtoeter.Ruckdeschel@itwm.fraunhofer.de">eter.Ruckdeschel@itwm.fraunhofer.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 22, 201-223.
Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves. Mathematical Methods in Statistics 14(1), 105-131.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness.  Bayreuth: Dissertation.

参见----------See Also----------

asGRisk-class, asMSE-class, asUnOvShoot-class, ContIC-class,
asGRisk-class，asMSE-class，asUnOvShoot-class，ContIC-class，

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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