getBiasIC(RobAStBase)
getBiasIC()所属R语言包:RobAStBase
Generic function for the computation of the asymptotic bias for an IC
用于IC的渐近偏差计算的通用函数
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Generic function for the computation of the asymptotic bias for an IC.
泛型函数为计算用于IC的渐近偏置。
用法----------Usage----------
getBiasIC(IC, neighbor, ...)
## S4 method for signature 'IC,UncondNeighborhood'
getBiasIC(IC, neighbor, L2Fam, biastype = symmetricBias(),
normtype = NormType(), tol = .Machine$double.eps^0.25, numbeval = 1e5)
参数----------Arguments----------
参数:IC
object of class "InfluenceCurve"
对象的类"InfluenceCurve"
参数:neighbor
object of class "Neighborhood".
对象类"Neighborhood"。
参数:...
additional parameters
额外的参数
参数:L2Fam
object of class "L2ParamFamily".
对象类"L2ParamFamily"。
参数:biastype
object of class "BiasType"
对象的类"BiasType"
参数:normtype
object of class "NormType"
对象的类"NormType"
参数:tol
the desired accuracy (convergence tolerance).
所需的精度(收敛宽容)。
参数:numbeval
number of evalation points.
数量的evalation点。
值----------Value----------
The bias of the IC is computed.
计算的IC的偏压。
方法----------Methods----------
IC = "IC", neighbor = "UncondNeighborhood" determines the as. bias by random evaluation of the IC; this random evaluation is done by the internal S4-method .evalBiasIC; this latter dispatches according to the signature IC, neighbor, biastype.<br> For signature IC="IC", neighbor = "ContNeighborhood", biastype = "BiasType", also an argument normtype is used to be able to use self- or information standardizing norms; besides this the signatures IC="IC", neighbor = "TotalVarNeighborhood", biastype = "BiasType", IC="IC", neighbor = "ContNeighborhood", biastype = "onesidedBias", and IC="IC", neighbor = "ContNeighborhood", biastype = "asymmetricBias" are implemented.
IC =“IC”,邻居“UncondNeighborhood”,决定作为。偏见的IC随机评价;随机评估是由内部S4方法.evalBiasIC;后者调度的签名IC, neighbor, biastype。<BR>对签名IC="IC", neighbor = "ContNeighborhood", biastype = "BiasType",也参数normtype能够使用自我或信息标准化规范,除了这个签名IC="IC", neighbor = "TotalVarNeighborhood", biastype = "BiasType",IC="IC", neighbor = "ContNeighborhood", biastype = "onesidedBias"和IC="IC", neighbor = "ContNeighborhood", biastype = "asymmetricBias"来实现。
注意----------Note----------
This generic function is still under construction.
这个通用的功能尚在建设中。
(作者)----------Author(s)----------
Peter Ruckdeschel <a href="mailtoeter.Ruckdeschel@itwm.fraunhofer.de">eter.Ruckdeschel@itwm.fraunhofer.de</a>
参考文献----------References----------
Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor. Verw. Geb. 10:269–278.
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.
Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Bias of M-estimators on Neighborhoods.
参见----------See Also----------
getRiskIC-methods, InfRobModel-class
getRiskIC-methods,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。
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。
|