找回密码
 注册
查看: 565|回复: 0

R语言 ROptEst包 cniperCont()函数中文帮助文档(中英文对照)

[复制链接]
发表于 2012-9-27 23:14:04 | 显示全部楼层 |阅读模式
cniperCont(ROptEst)
cniperCont()所属R语言包:ROptEst

                                         Generic Functions for Computation and Plot of Cniper Contamination
                                         通用函数的计算和绘图Cniper污染

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

These generic functions and their methods can be used to determine cniper  contamination as well as cniper points. That is, under which (Dirac)  contamination is the risk of one procedure larger than the risk of some other procedure.
这些通用的功能和它们的方法可以用来确定cniper的污染以及cniper点。也就是说,根据该(狄拉克)的污染是一个过程的风险大于其他一些过程的风险。


用法----------Usage----------


cniperCont(IC1, IC2, L2Fam, neighbor, risk, ...)
## S4 method for signature 'IC,IC,L2ParamFamily,ContNeighborhood,asMSE'
cniperCont(IC1,
      IC2, L2Fam, neighbor, risk, lower, upper, n = 101)

cniperPoint(L2Fam, neighbor, risk, ...)
## S4 method for signature 'L2ParamFamily,ContNeighborhood,asMSE'
cniperPoint(L2Fam,
      neighbor, risk, lower, upper)

cniperPointPlot(L2Fam, neighbor, risk, ...)
## S4 method for signature 'L2ParamFamily,ContNeighborhood,asMSE'
cniperPointPlot(L2Fam,
      neighbor, risk, lower, upper, n = 101, ...)



参数----------Arguments----------

参数:IC1
object of class IC
对象的类IC


参数:IC2
object of class IC
对象的类IC


参数:L2Fam
object of class L2ParamFamily
对象的类L2ParamFamily


参数:neighbor
object of class Neighborhood
对象的类Neighborhood


参数:risk
object of class RiskType
对象的类RiskType


参数:...
additional parameters (in particular to be passed on to plot).
其他参数(特别是转嫁到plot)。


参数:lower, upper
the lower and upper end points of the  contamination interval.
下部和上部终点污染间隔。


参数:n
number of points between lower and upper
数点之间lower和upper


Details

详细信息----------Details----------

In case of cniperCont the difference between the risks of two ICs  is plotted.
在箱子cniperCont绘制两个IC之间的差异的风险。

The function cniperPoint can be used to determine cniper points. That is, points such that the optimally robust estimator has smaller minimax risk than the classical optimal estimator under  contamination with Dirac measures at the cniper points.
功能cniperPoint可以用来确定cniper点。也就是说,例如,最优鲁棒估计有较小的极大极小风险比传统的最优估计下污染与狄拉克措施在cniper点。

As such points might be difficult to find, we provide the function cniperPointPlot which can be used to obtain a plot of the risk difference; in this function the usual arguments for plot can be used. For arguments col, lwd, vectors can be used; then the first coordinate is taken for the curve, the second one for the balancing line. For argument lty, a list can be used; its first component is then taken for the curve, the second one for the balancing line.
由于这些点可能是很难找到的,我们提供的功能cniperPointPlot这可以被用来获得一个图的风险差异,在这个函数中的常用参数plot都可以使用。有关的参数col,lwd,向量可以使用,然后被第一坐标的曲线,所述第二平衡线之一。参数lty,列表可以使用它的第一组分,然后采取的曲线,所述第二平衡线之一。

For more details about cniper contamination and cniper points we refer  to Section~3.5 of Kohl et al. (2008) as well as Ruckdeschel (2004) and  the Introduction of Kohl (2005).
更详细的cniper的污染和cniper点,我们请参阅第~3.5科尔等人。 (2008年),以及Ruckdeschel(2004)和科尔(2005年)的介绍。


值----------Value----------

invisible() resp. cniper point is returned.
无形的()分别。点返回cniper。


(作者)----------Author(s)----------


Matthias Kohl <a href="mailto:Matthias.Kohl@stamats.de">Matthias.Kohl@stamats.de</a>



参考文献----------References----------

Kohl, M. and Ruckdeschel, H. and Rieder, H. (2008). Infinitesimally  Robust Estimation in General Smoothly Parametrized Models. Unpublished Manuscript.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness.  Bayreuth: Dissertation.
Ruckdeschel, P. (2004). Higher Order Asymptotics for the MSE of M-Estimators on Shrinking Neighborhoods. Unpublished Manuscript.

实例----------Examples----------


## cniper contamination[#cniper污染]
P <- PoisFamily(lambda = 4)
RobP1 <- InfRobModel(center = P, neighbor = ContNeighborhood(radius = 0.1))
IC1 <- optIC(model=RobP1, risk=asMSE())
RobP2 <- InfRobModel(center = P, neighbor = ContNeighborhood(radius = 1))
IC2 <- optIC(model=RobP2, risk=asMSE())
cniperCont(IC1 = IC1, IC2 = IC2, L2Fam = P,
           neighbor = ContNeighborhood(radius = 0.5),
           risk = asMSE(),
           lower = 0, upper = 8, n = 101)

## cniper point plot[#cniper(点图)]
cniperPointPlot(P, neighbor = ContNeighborhood(radius = 0.5),
                risk = asMSE(), lower = 0, upper = 10)

## cniper point[#cniper点]
cniperPoint(P, neighbor = ContNeighborhood(radius = 0.5),
            risk = asMSE(), lower = 0, upper = 4)
cniperPoint(P, neighbor = ContNeighborhood(radius = 0.5),
            risk = asMSE(), lower = 4, upper = 8)

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。
回复

使用道具 举报

您需要登录后才可以回帖 登录 | 注册

本版积分规则

手机版|小黑屋|生物统计家园 网站价格

GMT+8, 2024-11-25 20:46 , Processed in 0.020004 second(s), 15 queries .

Powered by Discuz! X3.5

© 2001-2024 Discuz! Team.

快速回复 返回顶部 返回列表