getInfRobIC(ROptEstOld)
getInfRobIC()所属R语言包：ROptEstOld
Generic Function for the Computation of Optimally Robust ICs
通用函数的计算最理想的强大的集成电路
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Generic function for the computation of optimally robust ICs in case of infinitesimal robust models. This function is rarely called directly.
强大的芯片的情况下的无穷可靠的模型计算最佳的通用功能。很少直接调用此函数。
用法----------Usage----------
getInfRobIC(L2deriv, risk, neighbor, ...)
## S4 method for signature 'UnivariateDistribution,asCov,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,asCov,TotalVarNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
## S4 method for signature 'RealRandVariable,asCov,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,asBias,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,asBias,TotalVarNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,asBias,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,asHampel,UncondNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,asHampel,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,asGRisk,UncondNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,asGRisk,ContNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,asUnOvShoot,UncondNeighborhood'
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
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：...
additional parameters.
附加参数。
参数：Distr
object of class "Distribution".
对象类"Distribution"。
参数：symm
logical: indicating symmetry of L2deriv.
逻辑：表示对称的L2deriv。
参数：DistrSymm
object of class "DistributionSymmetry".
对象类"DistributionSymmetry"。
参数：L2derivSymm
object of class "FunSymmList".
对象类"FunSymmList"。
参数：L2derivDistrSymm
object of class "DistrSymmList".
对象类"DistrSymmList"。
参数：Finfo
Fisher information matrix.
Fisher信息矩阵。
参数：z.start
initial value for the centering constant.
定心常数的初始值。
参数：A.start
initial value for the standardizing matrix.
标准化矩阵的初始值。
参数：trafo
matrix: transformation of the parameter.
矩阵变换的参数。
参数：upper
upper bound for the optimal clipping bound.
上界的最佳剪辑约束。
参数：maxiter
the maximum number of iterations.
最大迭代次数。
参数：tol
the desired accuracy (convergence tolerance).
所需的精度（收敛宽容）。
参数：warn
logical: print warnings.
逻辑：打印警告。
值----------Value----------
The optimally robust IC is computed.
计算最优鲁棒的IC。
方法----------Methods----------
L2deriv = "UnivariateDistribution", risk = "asCov", neighbor = "ContNeighborhood" computes the classical optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”风险=的“asCov”邻居=“ContNeighborhood”的计算一维参数未知的经典最优L2微参数家庭的影响曲线。
L2deriv = "UnivariateDistribution", risk = "asCov", neighbor = "TotalVarNeighborhood" computes the classical optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”风险=的“asCov”邻居=“TotalVarNeighborhood”的计算一维参数未知的经典最优L2微参数家庭的影响曲线。
L2deriv = "RealRandVariable", risk = "asCov", neighbor = "ContNeighborhood" computes the classical optimal influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable的”风险=“asCov”的，邻居=“ContNeighborhood”计算的经典最优L2微参数家庭与未知的的k维参数（k > 1）的潜在分布的影响曲线单变量。
L2deriv = "UnivariateDistribution", risk = "asBias", neighbor = "ContNeighborhood" computes the bias optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”风险=的“asBias”邻居=“ContNeighborhood”的计算一维参数未知的偏见的最佳L2微参数家庭的影响曲线。
L2deriv = "UnivariateDistribution", risk = "asBias", neighbor = "TotalVarNeighborhood" computes the bias optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”风险=的“asBias”邻居=“TotalVarNeighborhood”的计算一维参数未知的偏见的最佳L2微参数家庭的影响曲线。
L2deriv = "RealRandVariable", risk = "asBias", neighbor = "ContNeighborhood" computes the bias optimal influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable的”风险=的“asBias”邻居=“ContNeighborhood”的计算偏置最佳的影响力与未知的的k维参数（k > 1）的潜在分布曲线L2微参数家庭单变量。
L2deriv = "UnivariateDistribution", risk = "asHampel", neighbor = "UncondNeighborhood" computes the optimally robust influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”，风险的“asHampel”邻居=“UncondNeighborhood”的L2微参数家庭与未知的一维参数计算最优强大的影响力曲线。
L2deriv = "RealRandVariable", risk = "asHampel", neighbor = "ContNeighborhood" computes the optimally robust influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable的”风险=“asHampel”的，邻居=“ContNeighborhood”计算最优强大的影响力，与未知的的k维参数（k > 1）的潜在分布曲线L2微参数家庭单变量。
L2deriv = "UnivariateDistribution", risk = "asGRisk", neighbor = "UncondNeighborhood" computes the optimally robust influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”，风险的“asGRisk”邻居=“UncondNeighborhood”的L2微参数家庭与未知的一维参数计算最优强大的影响力曲线。
L2deriv = "RealRandVariable", risk = "asGRisk", neighbor = "ContNeighborhood" computes the optimally robust influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable的”风险=“asGRisk”的，邻居=“ContNeighborhood”计算最优强大的影响力，与未知的的k维参数（k > 1）的潜在分布曲线L2微参数家庭单变量。
L2deriv = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "UncondNeighborhood" computes the optimally robust influence curve for one-dimensional L2 differentiable parametric families and asymptotic under-/overshoot risk.
L2deriv =的“UnivariateDistribution”风险=的“asUnOvShoot”邻居=“UncondNeighborhood”的计算一维L2可微分的参数化家庭和渐近under-/overshoot的风险的最佳强大的影响曲线。
（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: 106–115.
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----------
InfRobModel-class
InfRobModel-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 23:07:40
