robpredict(rsae)
robpredict()所属R语言包：rsae
Robust prediction of random effects, fixed effects, and area-specific means
鲁棒预测的随机效应，固定效应和领域的具体办法，
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function robpredict robustly predicts the random effects, fixed effects, and area-specific means under the model. As concerned with robustly predicting the realizations of the random effects, we rely on the method of Copt and Victoria-Feser (cf. Heritier et al., 2009, 113–114); not the method of Sinha and Rao (2009).
函数robpredict稳健预测模型下随机效应，固定效应和区域的具体手段。至于强劲预测的随机效果的实现，我们依靠的科普特人的方法和维多利亚 - Feser的（参见Heritier等，2009，113-114）;辛哈和Rao（2009）的方法。
用法----------Usage----------
robpredict(fit, areameans=NULL, k=NULL, reps=NULL)
## S3 method for class 'meanssaemodel'
print(x, digits=4, ...)
## S3 method for class 'meanssaemodel'
plot(x, y=NULL, type="e", sort=NULL, ...)
## S3 method for class 'meanssaemodel'
residuals(object, ...)
参数----------Arguments----------
参数：fit
a fitted SAE model; object of class fitsaemodel
一个装SAE模型对象的类fitsaemodel
参数：areameans
numeric matrix (typically, with area-level means); the no. of rows must be equal to the no. of areas; the no. of columns must be equal to the no. of fixed-effects coefficients (incl. intercept). By default: areadata=NULL, i.e., predictions are based on those data that have been used to estimate the model.
数字矩阵（通常情况下，区级手段）;没有。行必须等于无。区域;没有了。列必须有等于无。的固定效应系数（含截距）。默认情况下：areadata=NULL，即预测是根据这些数据已被用来估计模型。
参数：k
robustness tuning constant (of the Huber psi-function) for robust prediction. Notice that k does not necessarily be the same as the k that has been used in fitsaemodel. By default, k is equal to the tuning constant used in estimating the model parameters.
鲁棒性时间常数（胡贝尔psi的功能）为强健预测。注意，k不一定是相同的k已用于fitsaemodel。默认情况下，k是相等的时间常数，用于估计模型的参数。
参数：reps
number (integer) of bootstrap replicates for mean squared prediction error; default: reps=NULL
重复数字（整数）的引导均方预测误差;默认：reps=NULL
参数：x
object of the class "meanssaemodel"; this argument is only used in the print method.
类的对象"meanssaemodel"，这种说法只用在print方法。
参数：digits
integer, defining the number of decimal places to be shown in the print method (default: digits=4)
整数，显示在print方法定义的小数位数（默认：digits=4）
参数：y
has no meaning, yet! (default: y=NULL; needs to included in the args list, because it is part of plot's generic arg definition)
已经没有任何意义，但！ （默认：y=NULL;需要包含的参数列表中，因为它是的图的通用ARG定义的一部分）
参数：type
character specifying the plot method; either "e" (error bars; default) or "l" (lines).
字符，指定plot方法是"e"（误差线，默认）或"l"（系）。
参数：sort
only used in the plot method; if sort="means", the predicted means are ploted in ascending order (default: sort=NULL); similarly, with sort="fixef" and sort="ranef" the predicted means are sorted along the fixed effects or the random effects, respectively
仅用于plot方法; sort="means"如果，预测的方法ploted按升序（默认值：sort=NULL），同样，与sort="fixef"和sort="ranef"预测的方法排序分别沿固定效应或随机效应，
参数：object
object of the class fitsaemodel; a fitted model used in the residuals method.
类的对象fitsaemodel;拟合模型的用于residuals方法。
参数：...
not used
不使用
Details
详细信息----------Details----------
The robpredict function enables the following modes of prediction:
robpredict功能，可以预测以下模式：
if areameans=NULL, then the predictions are exclusively based on the sample values,
如果areameans=NULL，然后预测完全是基于对样本值，
if robpredict is called with areameans (i.e., matrix with area-specific means of the auxiliary data of conformable size), then the fixed-effect predictions and thus also the predictions of the area-specific means are based on the auxiliary data,
如果robpredict被称为用areameans（即，矩阵的特定于区域的保形的大小的辅助数据的装置），然后固定效果的预测，由此也确定预测的区域的具体手段是的基础上的辅助数据，
if, in addition to specifying areameans, one specifies also the number of bootstrap replications (i.e., reps; some positive integer), the function computes area-specific mean square prediction error (MSPE) estimates for the area-level means. The MSPE is obtained, in line with Sinha and Rao (2009), from a (robust) parametric bootstrap; see Lahiri (2003) and Hall and Maiti (2006) for more details.
此外指定areameans的，如果在“指定的引导复制（即reps;正整数），该函数计算面积均方预测误差（MSPE）的估计区域级别的手段。辛哈和Rao（2009），MSPE是，从参数引导（强大）;拉希莉（2003年）和霍尔和买提（2006年）的更多细节。
The tuning constant k regulates the degree of robustness (i.e., degree of winsorization of the Huber psi-function) when predicting the random effects. If k is sufficiently large (ideally, if k is equal to infinity), the predictions correspond to the EBLUP.
的时间常数k调节程度的鲁棒性（即胡贝尔PSI-函数的极值调整的程度），当预测的随机效果。如果k是足够大的（理想的情况下，如果k是等于无穷大），预测对应的EBLUP。
值----------Value----------
Instance of the S3 class meanssaemodel
实例S3类meanssaemodel
（作者）----------Author(s)----------
Tobias Schoch
参考文献----------References----------
实例----------Examples----------
#generate the synthetic data/model[生成的合成数据/模型]
mymodel <- makedata()
#compute Huber M-estimation type estimates of the model "mymodel"[计算胡贝尔M-估计估计模式“mymodel”]
#robustness tuning constant k = 2[鲁棒性调整常数k = 2]
myfittedmodel <- fitsaemodel("huberm", mymodel, k=2)
myfittedmodel
#get a summary of the model[的模型中得到的摘要]
summary(myfittedmodel)
#robustly predict the random effects and the area-level means. [强劲预测的随机效应和区域级别手段。]
#Here, we choose the robustness tuning constant k equal to 1.8[在这里，我们选择的稳健性调整常数k等于1.8]
mypredictions <- robpredict(myfittedmodel, k=1.8)
mypredictions
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。
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发表于 2012-9-28 21:15:47
