anova.glmrob(robustbase)
anova.glmrob()所属R语言包：robustbase
Analysis of Robust Quasi-Deviance for "glmrob" Objects
为“glmrob”对象的鲁棒准越轨行为分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute an analysis of robust quasi-deviance table for one or more generalized linear models fitted by glmrob.
计算分析的强大的准偏差表的一个或多个广义线性模型拟合glmrob。
用法----------Usage----------
## S3 method for class 'glmrob'
anova(object, ..., test = c("Wald", "QD", "QDapprox"))
参数----------Arguments----------
参数：object, ...
objects of class glmrob, typically the result of a call to glmrob.
类的对象glmrob，通常调用glmrob的结果。
参数：test
a character string specifying the test statistic to be used. (Partially) matching one of "Wald", "QD" or "QDapprox". See Details.
一个字符的字符串指定的检验统计量被使用。 （部分）匹配的"Wald"，"QD"或"QDapprox"。查看详细信息。
Details
详细信息----------Details----------
Specifying a single object gives a sequential analysis of robust quasi-deviance table for that fit. That is, the reductions in the robust residual quasi-deviance as each term of the formula is added in turn are given in as the rows of a table. (Currently not yet implemented.)
指定一个单一的对象提供了一个强大的准偏差的表，适合序列分析。也就是说，鲁棒残余准偏差行为作为下式的每个术语的减少反过来被添加为一个表的行中给出。 （目前尚未实现。）
If more than one object is specified, the table has a row for the residual quasi-degrees of freedom (However, this information is never used in the asymptotic tests). For all but the first model, the change in degrees of freedom and robust quasi-deviance is also given. (This only makes statistical sense if the models are nested.) It is conventional to list the models from smallest to largest, but this is up to the user.
如果一个以上的对象被指定时，表中有一个排残余准自由度（然而，这个信息是从未使用过在渐近测试）。所有，但第一种模式，变化程度的自由和强大的准偏差。 （这不仅使统计意义上的模型是嵌套的。），它是传统列出的车型，从最小到最大，但是这是由用户。
In addition, the table will contain test statistics and P values comparing the reduction in robust quasi-deviance for the model on the row to that on top of it. For all robust fitting methods, the “Wald”-type test between two models can be applied (test = "Wald").
此外，该表将包含检验统计量和P值比较强大的准偏差的减少，该行的模型，在它的上面。所有强大的拟合方法，“沃尔德”型的测试两种模型之间可以应用（test = "Wald"）。
When using Mallows or Huber type robust estimators (method="Mqle" in glmrob), then there are additional test methods. One is the robust quasi-deviance test (test = "QD"), as described by Cantoni and Ronchetti (2001). The asymptotic distribution is approximated by a chi-square distibution. Another test (test = "QDapprox") is based on a quadratic approximation of the robust quasi-deviance test statistic. Its asymptotic distribution is chi-square (see the reference).
锦葵或胡贝尔的稳健估计量（当使用method="Mqle"glmrob），则有额外的测试方法。一个是强大的准偏差测试（test = "QD"），坎托尼和龙凯蒂（2001）所描述的。渐近分布近似卡方发行套装。另一项测试（test = "QDapprox"）是基于强大的准偏差的检验统计量的二次近似的。它的渐近分布是卡方（见参考）。
The comparison between two or more models by anova.glmrob will only be valid if they are fitted to the same dataset and by the same robust fitting method using the same tuning constant c (tcc in glmrob).
比较两个或两个以上模型anova.glmrob只会是有效的，如果它们安装到相同的数据集，并同样强大的拟合方法使用相同的时间常数c（tcc glmrob“）。
值----------Value----------
Basically, an object of class anova inheriting from class data.frame.
基本上，类的一个对象anova继承类data.frame的。
（作者）----------Author(s)----------
Andreas Ruckstuhl
参考文献----------References----------
Robust Inference for Generalized Linear Models. JASA 96 (455), 1022–1030.
Analysis of Robust Quasi-deviances for Generalized Linear Models. Journal of Statistical Software 10, http://www.jstatsoft.org/v10/i04
参见----------See Also----------
glmrob, anova.
glmrob，anova。
实例----------Examples----------
## Binomial response -----------[＃二项式响应-----------]
data(carrots)
Cfit2 <- glmrob(cbind(success, total-success) ~ logdose + block,
family=binomial, data=carrots, method="Mqle",
control=glmrobMqle.control(tcc=1.2))
summary(Cfit2)
Cfit4 <- glmrob(cbind(success, total-success) ~ logdose * block,
family=binomial, data=carrots, method="Mqle",
control=glmrobMqle.control(tcc=1.2))
anova(Cfit2, Cfit4, test="Wald")
anova(Cfit2, Cfit4, test="QD")
anova(Cfit2, Cfit4, test="QDapprox")
## Poisson response ------------[＃的泊松反应------------]
data(epilepsy)
Efit2 <- glmrob(Ysum ~ Age10 + Base4*Trt, family=poisson, data=epilepsy,
method="Mqle", control=glmrobMqle.control(tcc=1.2,maxit=100))
summary(Efit2)
Efit3 <- glmrob(Ysum ~ Age10 + Base4 + Trt, family=poisson, data=epilepsy,
method="Mqle", control=glmrobMqle.control(tcc=1.2,maxit=100))
anova(Efit3, Efit2, test = "Wald")
anova(Efit3, Efit2, test = "QD")
anova(Efit3, Efit2, test = "QDapprox")
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。
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发表于 2012-9-27 22:06:57
