getReq(ROptEst)
getReq()所属R语言包：ROptEst
getReq – computation of the radius interval where IC1 is better than IC2
getReq - IC1是比IC2的半径间隔的计算
译者：生物统计家园网 机器人LoveR
描述----------Description----------
(tries to) compute a radius interval where IC1 is better than IC2
（试图）计算IC1是一个半径间隔比IC2
用法----------Usage----------
getReq(Risk,neighbor,IC1,IC2,n=1,upper=15)
参数----------Arguments----------
参数：Risk
an object of class "asGRisk" – the risk at which IC1 is better than IC2.
对象的类"asGRisk" - IC1是比IC2的风险。
参数：neighbor
object of class "Neighborhood"; the neighborhood at which to compute the bias.
计算对象的类"Neighborhood";附近的偏差。
参数：IC1
some IC of class "IC"
一些IC类"IC"
参数：IC2
some IC of class "IC"
一些IC类"IC"
参数：n
the sample size; by default set to 1; then the radius interval refers to starting radii in the shrinking neighborhood setting of Rieder[94]. Otherwise the radius interval is scaled down accordingly.
的样本大小，默认设置为1，然后半径间隔是指在里德尔的的附近设置萎缩的开始半径[94]。否则，半径间隔相应缩减。
参数：upper
the upper bound of the radius interval in which to search
半径区间的上限要在其中搜索
值----------Value----------
The radius interval (given by its endpoints) where IC1 is better than IC2 according to the risk. In case IC2 is better than IC1 as to both variance and bias,
的的半径间隔时间（其端点）IC1是比IC2根据风险。如果IC2是更好的比IC1，方差和偏差，
（作者）----------Author(s)----------
Peter Ruckdeschel <a href="mailto:peter.ruckdeschel@fraunhofer.itwm.de">peter.ruckdeschel@fraunhofer.itwm.de</a>
参考文献----------References----------
Hampel et al. (1986) Robust Statistics. The Approach Based on Influence Functions. New York: Wiley.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
实例----------Examples----------
N0 <- NormLocationFamily(mean=2, sd=3)
## L_2 family + infinitesimal neighborhood[＃L_2家庭+无穷小附近]
neighbor <- ContNeighborhood(radius = 0.5)
N0.Rob1 <- InfRobModel(center = N0, neighbor = neighbor)
## OBRE solution (ARE 95%)[＃OBRE解决方案（95％）]
N0.ICA <- optIC(model = N0.Rob1, risk = asAnscombe(.95))
## MSE solution[＃MSE解决方案]
N0.ICM <- optIC(model=N0.Rob1, risk=asMSE())
## RMX solution[＃RMX解决方案]
N0.ICR <- radiusMinimaxIC(L2Fam=N0, neighbor=neighbor,risk=asMSE())
getReq(asMSE(),neighbor,N0.ICA,N0.ICM,n=1)
getReq(asMSE(),neighbor,N0.ICA,N0.ICM,n=30)
getReq(asL1(),neighbor,N0.ICA,N0.ICM,n=30)
getReq(asL4(),neighbor,N0.ICA,N0.ICM,n=30)
getReq(asMSE(),neighbor,N0.ICA,N0.ICR,n=30)
getReq(asL1(),neighbor,N0.ICA,N0.ICR,n=30)
getReq(asL4(),neighbor,N0.ICA,N0.ICR,n=30)
getReq(asMSE(),neighbor,N0.ICM,N0.ICR,n=30)
### when to use MAD and when Qn [＃＃当使用MAD当qN]
## for Qn, see C. Croux, P. Rousseeuw (1993). Alternatives to the Median [编号为QN，请参阅：C.，克鲁，P. Rousseeuw（1993）。替代的中位数的]
## Absolute Deviation, JASA 88(424):1273-1283[＃绝对偏差，JASA 88（424）:1273-1283]
L2M <- NormScaleFamily()
IC.mad <- makeIC(function(x)sign(abs(x)-qnorm(.75)),L2M)
d.qn <- (2^.5*qnorm(5/8))^-1
IC.qn <- makeIC(function(x) d.qn*(1/4 - pnorm(x+1/d.qn) + pnorm(x-1/d.qn)), L2M)
getReq(asMSE(), neighbor, IC.mad, IC.qn)
# => MAD is better once r > 0.5144 (i.e. for more than 2 outliers for n = 30)[=> MAD是一次R> 0.5144（即超过2离群为n = 30）]
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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 23:17:09
