getInfStand(ROptEst)
getInfStand()所属R语言包：ROptEst
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----------
getInfStand(L2deriv, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType'
getInfStand(L2deriv,
neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'UnivariateDistribution,TotalVarNeighborhood,BiasType'
getInfStand(L2deriv,
neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'RealRandVariable,UncondNeighborhood,BiasType'
getInfStand(L2deriv,
neighbor, biastype, Distr, A.comp, cent, trafo, w)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType'
getInfStand(L2deriv,
neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType'
getInfStand(L2deriv,
neighbor, biastype, clip, cent, trafo)
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：neighbor
object of class "Neighborhood"
对象的类"Neighborhood"
参数：biastype
object of class "BiasType"
对象的类"BiasType"
参数：...
additional parameters
额外的参数
参数：clip
optimal clipping bound.
最佳剪裁的约束。
参数：cent
optimal centering constant.
最优的中心不变。
参数：Distr
object of class "Distribution".
对象类"Distribution"。
参数：trafo
matrix: transformation of the parameter.
矩阵变换的参数。
参数：A.comp
matrix: indication which components of the standardizing matrix have to be computed.
矩阵：指示哪些组件标准化矩阵以计算。
参数：w
object of class RobWeight; current weight
对象的类RobWeight;目前的体重
值----------Value----------
The standardizing matrix is computed.
的标准化矩阵计算。
方法----------Methods----------
L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType" computes standardizing matrix for symmetric bias.
L2deriv =的“UnivariateDistribution”，邻居=“ContNeighborhood”，biastype =“BiasType”的计算标准化矩阵，对称的偏差。
L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType" computes standardizing matrix for symmetric bias.
L2deriv =的“UnivariateDistribution”，邻居=“TotalVarNeighborhood”，biastype =“BiasType”的计算标准化矩阵，对称的偏差。
L2deriv = "RealRandVariable", neighbor = "UncondNeighborhood", biastype = "BiasType" computes standardizing matrix for symmetric bias.
L2deriv =“RealRandVariable”，邻居=“UncondNeighborhood”，biastype。=“BiasType”的计算标准化矩阵，对称的偏差。
L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias" computes standardizing matrix for onesided bias.
L2deriv =的“UnivariateDistribution”，邻居=“ContNeighborhood”，biastype =“onesidedBias”的计算标准化矩阵片面的偏见。
L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias" computes standardizing matrix for asymmetric bias.
L2deriv =的“UnivariateDistribution”，邻居=“ContNeighborhood”，biastype =“asymmetricBias”的计算规范矩阵的非对称偏差。
（作者）----------Author(s)----------
Matthias Kohl <a href="mailto:Matthias.Kohl@stamats.de">Matthias.Kohl@stamats.de</a>,
Peter Ruckdeschel <a href="mailto eter.Ruckdeschel@itwm.fraunhofer.de"> eter.Ruckdeschel@itwm.fraunhofer.de</a>
参考文献----------References----------
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
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----------
ContIC-class, TotalVarIC-class
ContIC-class，TotalVarIC-class
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 23:16:17
