showdown(RobLox)
showdown()所属R语言包：RobLox
Estimator Showdown by Monte-Carlo Study.
用Monte-Carlo研究估计摊牌。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function showdown can be used to perform Monte-Carlo studies comparing a competitor with rmx estimators in case of normal location and scale. In addition, maximum likelihood (ML) estimators (mean and sd) and median and MAD are computed. The comparison is based on the empirical MSE.
功能showdown可以用来执行蒙特卡罗研究比较RMX的估计的情况下，正常的位置和规模的竞争对手。此外，最大似然（ML）估计量（均值和方差）和中位数和MAD计算。该比较的基础上的经验的MSE。
用法----------Usage----------
showdown(n, M, eps, contD, seed = 123, estfun, estMean, estSd,
eps.lower = 0, eps.upper = 0.05, steps = 3L, fsCor = TRUE,
plot1 = FALSE, plot2 = FALSE, plot3 = FALSE)
参数----------Arguments----------
参数：n
integer; sample size, should be at least 3.
整数;样本大小，应该是至少为3。
参数：M
integer; Monte-Carlo replications.
整数;蒙地卡罗复制。
参数：eps
amount of contamination in [0, 0.5].
[0，0.5]中的污染物量。
参数：contD
object of class "UnivariateDistribution"; contaminating distribution.
对象的类"UnivariateDistribution";污染分布。
参数：seed
random seed.
随机种子。
参数：estfun
function to compute location and scale estimator; see details below.
函数来计算位置和规模估计，详见下文。
参数：estMean
function to compute location estimator; see details below.
函数来计算位置估计，详见下文。
参数：estSd
function to compute scale estimator; see details below.
函数来计算规模估计，详见下文。
参数：eps.lower
used by rmx estimator.
使用RMX估计。
参数：eps.upper
used by rmx estimator.
使用RMX估计。
参数：steps
integer; steps used for estimator construction.
整数，用于估计建设的步骤。
参数：fsCor
logical; use finite-sample correction.
逻辑;利用有限样本校正。
参数：plot1
logical; plot cdf of ideal and real distribution.
逻辑图民防部队的理想与现实的分布。
参数：plot2
logical; plot 20 (or M if M < 20) randomly selected samples.
逻辑图20（或M，如果M <20）随机抽取的样品。
参数：plot3
logical; generate boxplots of the results.
逻辑产生盒形图的结果。
Details
详细信息----------Details----------
Normal location and scale with mean = 0 and sd = 1 is used as ideal model (without restriction due to equivariance).
正常位置和规模，与平均值= 0和sd = 1被用作理想的模型（由于equivariance没有限制）。
Since there is no estimator which yields reliable results if 50 percent or more of the observations are contaminated, we use a modification where we re-simulate all samples including at least 50 percent contaminated data.
由于没有估计得到可靠的结果，如果50％或更多的意见被污染，我们使用了修改，在这里我们重新模拟样本，包括至少50％的污染数据。
If estfun is specified it has to compute and return a location and scale estimate (vector of length 2). One can also specify the location and scale estimator separately by using estMean and estSd where estMean computes and returns the location estimate and estSd the scale estimate.
如果estfun指定它的位置和规模估计（向量长度为2）计算并返回。你也可以使用指定的地点和规模估计分别estMean和estSd其中estMean的位置估计和estSd的的规模估计计算并返回。
We use funtion rowRoblox for the computation of the rmx estimator.
我们使用FUNTIONrowRoblox计算的RMX估计的。
值----------Value----------
Data.frame including empirical MSE (standardized by sample size n) and relMSE with respect to the rmx estimator.
数据框，包括经验MSE（标准的样本大小n）与的RMX估计的和relMSE。
（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. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing the Radius. Statistical Methods and Applications 17(1) 13-40. Extended version: http://www.stamats.de/RRlong.pdf
参见----------See Also----------
rowRoblox
rowRoblox
实例----------Examples----------
library(MASS)
## compare with Huber's Proposal 2[＃与胡贝尔的建议2]
showdown(n = 20, M = 100, eps = 0.02, contD = Norm(mean = 3, sd = 3),
estfun = function(x){ unlist(hubers(x)) },
plot1 = TRUE, plot2 = TRUE, plot3 = TRUE)
## compare with Huber M estimator with MAD scale[＃MAD规模与胡贝尔M估计]
showdown(n = 20, M = 100, eps = 0.02, contD = Norm(mean = 3, sd = 3),
estfun = function(x){ unlist(huber(x)) },
plot1 = TRUE, plot2 = TRUE, plot3 = TRUE)
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 21:10:47
