predict.glmrob(robustbase)
predict.glmrob()所属R语言包：robustbase
Predict Method for Robust GLM ("glmrob") Fits
预测方法的鲁棒GLM（“glmrob”），适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Obtains predictions and optionally estimates standard errors of those predictions from a fitted robust generalized linear model (GLM) object.
获得的预测，并选择性地估计，这些预测从一个装有强大的广义线性模型（GLM）对象的标准错误的。
用法----------Usage----------
## S3 method for class 'glmrob'
predict(object, newdata = NULL,
type = c("link", "response", "terms"), se.fit = FALSE,
dispersion = NULL, terms = NULL, na.action = na.pass, ...)
参数----------Arguments----------
参数：object
a fitted object of class inheriting from "glmrob".
一个装有对象的类继承自"glmrob"。
参数：newdata
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used.
可选的数据框中寻找变量，用以预测。如果省略该参数，拟合的线性预测。
参数：type
the type of prediction required. The default is on the scale of the linear predictors; the alternative "response" is on the scale of the response variable. Thus for a default binomial model the default predictions are of log-odds (probabilities on logit scale) and type = "response" gives the predicted probabilities. The "terms" option returns a matrix giving the fitted values of each term in the model formula on the linear predictor scale. The value of this argument can be abbreviated.
所需的预测的类型。默认情况下是上规模的线性预测替代"response"是上规模的响应变量。因此，对于一个默认的二项式模型默认的预测是记录的可能性（概率上罗吉特规模）和type = "response"给出了预测概率。 "terms"选项返回一个矩阵，每学期提供的拟合值的线性预测模型公式规模。这个参数的值，可以缩写。
参数：se.fit
logical switch indicating if standard errors are required.
如果标准错误的逻辑交换机。
参数：dispersion
the dispersion of the GLM fit to be assumed in computing the standard errors. If omitted, that returned by summary applied to the object is used.
的分散体的GLM配合要假定，计算标准误差。如果省略，则返回summary使用对象的。
参数：terms
with type="terms" by default all terms are returned. A character vector specifies which terms are to be returned
type="terms"默认情况下，所有条款均返回。一个字符向量指定要返回其条款
参数：na.action
function determining what should be done with missing values in newdata. The default is to predict NA.
功能决定什么应该做的遗漏值newdata。默认值是预测NA。
参数：...
optional further arguments, currently simply passed to predict.lmrob().
可选的进一步论证，目前简单的通过predict.lmrob()。
值----------Value----------
If se = FALSE, a vector or matrix of predictions. If se = TRUE, a list with components
如果se = FALSE，一个向量或矩阵的预测。如果se = TRUE，组件的列表
参数：fit
Predictions
预测
参数：se.fit
Estimated standard errors
估计标准误差
参数：residual.scale
A scalar giving the square root of the dispersion used in computing the standard errors.
标量的分散体，用于计算标准误差的平方根。
（作者）----------Author(s)----------
Andreas Ruckstuhl
参见----------See Also----------
glmrob() to fit these robust GLM models, residuals.glmrob() and other methods; predict.lm(), the method used for a non-robust fit.
glmrob()，以适应这些强大的GLM模型，residuals.glmrob()和其他方法; predict.lm()，为一个不健壮，适合采用的方法。
实例----------Examples----------
data(carrots)
## simplistic testing & training:[＃简单的测试和培训：]
i.tr <- sample(24, 20)
fm1 <- glmrob(cbind(success, total-success) ~ logdose + block,
family = binomial, data = carrots, subset = i.tr)
fm1
predict(fm1, carrots[-i.tr, ]) # --> numeric vector[ - >数字矢量]
predict(fm1, carrots[-i.tr, ],
type="response", se = TRUE)# -> a list[ - >列表]
data(vaso)
Vfit <- glmrob(Y ~ log(Volume) + log(Rate), family=binomial, data=vaso)
newd <- expand.grid(Volume = (V. <- seq(.5, 4, by = 0.5)),
Rate = (R. <- seq(.25,4, by = 0.25)))
p <- predict(Vfit, newd)
filled.contour(V., R., matrix(p, length(V.), length(R.)),
main = "predict(glmrob(., data=vaso))", xlab="Volume", ylab="Rate")
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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。
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发表于 2012-9-27 22:13:08
