minmaxBias(ROptEst)
minmaxBias()所属R语言包:ROptEst
Generic Function for the Computation of Bias-Optimally Robust ICs
通用功能的计算偏置最佳强大的集成电路
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Generic function for the computation of bias-optimally robust ICs in case of infinitesimal robust models. This function is rarely called directly.
偏置最佳强大的芯片的情况下的无穷可靠的模型计算的通用功能。很少直接调用此函数。
用法----------Usage----------
minmaxBias(L2deriv, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,asymmetricBias'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,onesidedBias'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo)
## S4 method for signature 'UnivariateDistribution,TotalVarNeighborhood,BiasType'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo)
## S4 method for signature 'RealRandVariable,ContNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, normtype, Distr, z.start, A.start, z.comp, A.comp,
Finfo, trafo, maxiter, tol, verbose = NULL)
## S4 method for signature 'RealRandVariable,TotalVarNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, normtype, Distr, z.start, A.start, z.comp, A.comp,
Finfo, trafo, maxiter, tol, verbose = NULL)
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".
对象类"Neighborhood"。
参数:biastype
object of class "BiasType".
对象类"BiasType"。
参数:normtype
object of class "NormType".
对象类"NormType"。
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: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:z.comp
logical indicator which indices need to be computed and which are 0 due to symmetry.
logical指示器需要计算哪个索引是0由于对称性。
参数:A.comp
matrix of logical indicator which indices need to be computed and which are 0 due to symmetry.
matrixlogical指标,需要计算的指数的,哪些是0由于对称性。
参数:trafo
matrix: transformation of the parameter.
矩阵变换的参数。
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:Finfo
Fisher information matrix.
Fisher信息矩阵。
参数:verbose
logical: if TRUE, some messages are printed
逻辑:如果TRUE,一些消息都印
值----------Value----------
The bias-optimally robust IC is computed.
偏置最佳状态的鲁棒IC计算。
方法----------Methods----------
L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType" computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”,邻居=“ContNeighborhood”,biastype =“BiasType”计算L2微一维参数未知参数家庭对称偏置曲线的偏置最佳的影响力。
L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias" computes the bias optimal influence curve for asymmetric bias for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”,邻居=“ContNeighborhood”,biastype =“asymmetricBias”计算最佳的偏见的影响L2微参数家庭与未知的一维参数曲线的非对称偏置。
L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType" computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv =的“UnivariateDistribution”,邻居=“TotalVarNeighborhood”,biastype =“BiasType”计算L2微一维参数未知参数家庭对称偏置曲线的偏置最佳的影响力。
L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType" computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable”,邻居=“ContNeighborhood”,biastype =“BiasType”的未知k维参数(k > 1),其中的计算偏置最佳的影响力为对称偏置曲线L2微参数家庭基本分布是一元的。
L2deriv = "RealRandVariable", neighbor = "TotalNeighborhood", biastype = "BiasType" computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families in a setting where we are interested in a p=1 dimensional aspect of an unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv =“RealRandVariable”,邻居=“TotalNeighborhood”,biastype =“BiasType”的计算L2微参数家庭设置我们感兴趣的是一个p=1的维方面的一个未知的最优偏置影响曲线对称偏置k维参数(k > 1)的基本分布是单变量。
(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: 106–115.
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----------
InfRobModel-class
InfRobModel-class
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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