getInfRobRegTypeIC(ROptRegTS)
getInfRobRegTypeIC()所属R语言包：ROptRegTS
Generic Function for the Computation of Optimally Robust Regression-Type ICs
通用函数计算的的最优稳健回归型集成电路
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Generic function for the computation of optimally robust regression-type ICs in case of infinitesimal robust models. This function is rarely called directly.
通用功能的最佳稳健回归型芯片的情况下的无穷可靠的模型计算。很少直接调用此函数。
用法----------Usage----------
getInfRobRegTypeIC(ErrorL2deriv, Regressor, risk, neighbor, ...)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asBias,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asBias,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asBias,Av1CondTotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,Distribution,asBias,Av2CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asCov,TotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,CondTotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,Av2CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asCov,Av1CondTotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution,Distribution,asGRisk,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,Distribution,asGRisk,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,Distribution,asGRisk,Av2CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,Distribution,asGRisk,Av1CondTotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,asBias,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,asBias,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,MultivariateDistribution,asBias,Av1CondTotalVarNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,Distribution,asBias,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorSymm, RegSymm, ErrorDistr, ErrorL2derivSymm,
ErrorL2derivDistrSymm, Finfo, trafo, upper, z.start, A.start, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,Distribution,asBias,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorSymm, RegSymm, ErrorDistr, ErrorL2derivSymm,
ErrorL2derivDistrSymm, Finfo, trafo, upper, z.start, A.start, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,Distribution,asCov,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorDistr, Finfo, trafo)
## S4 method for signature 'RealRandVariable,Distribution,asCov,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorDistr, Finfo, trafo)
## S4 method for signature 'RealRandVariable,Distribution,asGRisk,ContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorSymm, RegSymm, ErrorDistr, ErrorL2derivSymm,
ErrorL2derivDistrSymm, Finfo, trafo, upper, z.start, A.start, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable,Distribution,asGRisk,Av1CondContNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorSymm, RegSymm, ErrorDistr, ErrorL2derivSymm,
ErrorL2derivDistrSymm, Finfo, trafo, upper, z.start, A.start, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asUnOvShoot,UncondNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution,asUnOvShoot,CondNeighborhood'
getInfRobRegTypeIC(ErrorL2deriv,
Regressor, risk, neighbor, ErrorL2derivDistrSymm, RegSymm, Finfo, trafo,
upper, maxiter, tol, warn)
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：ErrorSymm
symmetry of ErrorDistr.
对称的ErrorDistr。
参数：ErrorL2derivDistrSymm
symmetry of ErrorL2derivDistr.
对称的ErrorL2derivDistr。
参数：RegSymm
symmetry of RegDistr.
对称的RegDistr。
参数：ErrorDistr
error distribution.
误差分布。
参数：ErrorL2derivSymm
symmetry of ErrorL2deriv.
对称的ErrorL2deriv。
参数：Finfo
Fisher information matrix.
Fisher信息矩阵。
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。
参数：z.start
initial value for the centering constant/function.
中心的常数/函数的初始值。
参数：A.start
initial value for the standardizing matrix.
标准化矩阵的初始值。
值----------Value----------
The optimally robust IC is computed.
计算最优鲁棒的IC。
方法----------Methods----------
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asBias", neighbor = "ContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=的“asBias”邻居=“ContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asBias", neighbor = "Av1CondContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=的“asBias”邻居=“Av1CondContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asBias", neighbor = "Av1CondTotalVarNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=的“asBias”邻居=“Av1CondTotalVarNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asBias", neighbor = "Av2CondContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asBias”邻居=“Av2CondContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "ContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“ContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asCov", neighbor = "TotalVarNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=的“asCov”邻居=“TotalVarNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "CondContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“CondContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "CondTotalVarNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“CondTotalVarNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "Av1CondContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“Av1CondContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "Av2CondContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“Av2CondContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asCov", neighbor = "Av1CondTotalVarNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“分配”，风险=的“asCov”邻居=“Av1CondTotalVarNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asGRisk", neighbor = "ContNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“风险分配”，=“asGRisk”的，邻居=“ContNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asGRisk", neighbor = "Av1CondContNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“风险分配”，=“asGRisk”的，邻居=“Av1CondContNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asGRisk", neighbor = "Av2CondContNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“风险分配”，=“asGRisk”的，邻居=“Av2CondContNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asGRisk", neighbor = "Av1CondTotalVarNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“风险分配”，=“asGRisk”的，邻居=“Av1CondTotalVarNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asBias", neighbor = "ContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=的“asBias”邻居=“ContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asBias", neighbor = "Av1CondContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=的“asBias”邻居=“Av1CondContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asBias", neighbor = "Av1CondTotalVarNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“MultivariateDistribution”的风险=的“asBias”邻居=“Av1CondTotalVarNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asBias", neighbor = "ContNeighborhood" computes the bias optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，风险的“asBias”邻居=“ContNeighborhood”的计算偏差的最佳L2微回归家庭的影响曲线。
ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asCov", neighbor = "ContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，风险的“asCov”邻居=“ContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asCov", neighbor = "Av1CondContNeighborhood" computes the classical optimal influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”，风险的“asCov”邻居=“Av1CondContNeighborhood”的计算经典的最优L2微回归家庭的影响曲线。
ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asGRisk", neighbor = "ContNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”风险=的“asGRisk”邻居=“ContNeighborhood”的计算曲线L2微回归家庭的最佳强大的影响力。
ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asGRisk", neighbor = "Av1CondContNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“RealRandVariable”，REGRESSOR =“分配”风险=的“asGRisk”邻居=“Av1CondContNeighborhood”的计算曲线L2微回归家庭的最佳强大的影响力。
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "UncondNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asUnOvShoot”的，邻居=“UncondNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "CondNeighborhood" computes the optimally robust influence curve for L2 differentiable regression-type families.
ErrorL2deriv =“UnivariateDistribution”，REGRESSOR =“UnivariateDistribution”的风险=“asUnOvShoot”的，邻居=“CondNeighborhood”计算最优强大的影响力，曲线L2微回归家庭。
（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----------
InfRobRegTypeModel-class
InfRobRegTypeModel-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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-27 23:23:43
