glm.diag.plots(boot)
glm.diag.plots()所属R语言包：boot
Diagnostics plots for generalized linear models
广义线性模型的诊断图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Makes plot of jackknife deviance residuals against linear predictor, normal scores plots of standardized deviance residuals, plot of approximate Cook statistics against leverage/(1-leverage), and case plot of Cook statistic.
使图的折刀偏差残差对线性预测，正常的分数标准偏差残差图，对利用/（1杠杆），Cook统计图近似库克统计图。
用法----------Usage----------
glm.diag.plots(glmfit, glmdiag = glm.diag(glmfit), subset = NULL,
iden = FALSE, labels = NULL, ret = FALSE)
参数----------Arguments----------
参数：glmfit
glm.object : the result of a call to glm()
glm.object：调用glm()一个结果
参数：glmdiag
Diagnostics of glmfit obtained from a call to glm.diag. If it is not supplied then it is calculated.
诊断glmfit调用glm.diag从获得。如果它没有提供，则计算。
参数：subset
Subset of data for which glm fitting performed: should be the same as the subset option used in the call to glm() which generated glmfit. Needed only if the subset= option was used in the call to glm.
子集data为glm装修进行：应该是作为subset调用glm()生成的glmfit在使用的选项相同。需在调用subset=只有glm选项。
参数：iden
A logical argument. If TRUE then, after the plots are drawn, the user will be prompted for an integer between 0 and 4. A positive integer will select a plot and invoke identify() on that plot. After exiting identify(), the user is again prompted, this loop continuing until the user responds to the prompt with 0. If iden is FALSE (default) the user cannot interact with the plots.
逻辑论证。如果TRUE然后，图绘制后，用户将被提示为0和4之间的整数。一个正整数，将选择一个图，并调用，图identify()。退出后identify()，再次提示用户，这个循环继续，直到用户响应提示0。如果iden是FALSE（默认）用户无法与图互动。
参数：labels
A vector of labels for use with identify() if iden is TRUE. If it is not supplied then the labels are derived from glmfit.
一个用identify()如果iden是TRUE使用标签的向量。如果它没有提供，则标签是根据从glmfit。
参数：ret
A logical argument indicating if glmdiag should be returned. The default is FALSE. </table>
一个逻辑论证表明glmdiag如果应退还。默认FALSE。 </ TABLE>
Details
详情----------Details----------
The diagnostics required for the plots are calculated by glm.diag. These are then used to produce the four plots on the current graphics device.
图所需的诊断计算glm.diag。这些都是当前图形设备上产生的四个图。
The plot on the top left is a plot of the jackknife deviance residuals against the fitted values.
在左上角的图，是一个对拟合值的的折刀偏差残差的图。
The plot on the top right is a normal QQ plot of the standardized deviance residuals. The dotted line is the expected line if the standardized residuals are normally distributed, i.e. it is the line with intercept 0 and slope 1.
右上方的图是一个正常的标准偏差残差的QQ图。虚线是预期的行，如果是正态分布的标准化残差，即它是截距0，斜率1线。
The bottom two panels are plots of the Cook statistics. On the left is a plot of the Cook statistics against the standardized leverages. In general there will be two dotted lines on this plot. The horizontal line is at 8/(n-2p) where n is the number of observations and p is the number of parameters estimated. Points above this line may be points with high influence on the model. The vertical line is at 2p/(n-2p) and points to the right of this line have high leverage compared to the variance of the raw residual at that point. If all points are below the horizontal line or to the left of the vertical line then the line is not shown.
上下两板是库克统计图。左边的是对标准化利用了库克统计图。一般会有两个虚线这个图。水平线是在8 /（N-2P），其中n是观测数，p是参数估计的数目。这条线以上的点可能是模型的影响高点。垂直线是2P /（N-2P）和指向此行的权利有高杠杆率相比，在这一点上的原始残余方差。如果所有的点下面的水平线或垂直线的左侧，然后行不显示。
The final plot again shows the Cook statistic this time plotted against case number enabling us to find which observations are influential.
最后的图再次表明库克统计，这段时间对情况编号策划使我们能够找到哪些意见是有影响的。
Use of iden=T is encouraged for proper exploration of these four plots as a guide to how well the model fits the data and whether certain observations have an unduly large effect on parameter estimates.
使用iden=T鼓励适当的探索，这四个图作为指导如何以及该模型适合数据和一定的观察是否有一个参数估计过大的影响。
值----------Value----------
If ret is TRUE then the value of glmdiag is returned otherwise there is no returned value.
如果ret是TRUE然后glmdiag的价值返回，否则是没有返回值。
副作用----------Side Effects----------
The current device is cleared and four plots are plotted by use of split.screen(c(2,2)). If iden is TRUE, interactive identification of points is enabled. All screens are closed, but not cleared, on termination of the function.
清除当前设备是四图绘制使用split.screen(c(2,2))。如果idenTRUE，交互式识别点启用。所有的屏幕被关闭，但不清除，终止功能。
参考文献----------References----------
Bootstrap Methods and Their Application. Cambridge University Press.
Statistical Theory and Modelling: In Honour of Sir David Cox D.V. Hinkley, N. Reid, and E.J. Snell (editors), 83–106. Chapman and Hall.
参见----------See Also----------
glm, glm.diag, identify
glm，glm.diag，identify
举例----------Examples----------
# In this example we look at the leukaemia data which was looked at in [在这个例子中，我们看在看着白血病数据]
# Example 7.1 of Davison and Hinkley (1997)[例如7.1戴维森和欣克利（1997）]
data(leuk, package = "MASS")
leuk.mod <- glm(time ~ ag-1+log10(wbc), family = Gamma(log), data = leuk)
leuk.diag <- glm.diag(leuk.mod)
glm.diag.plots(leuk.mod, leuk.diag)
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 2012-2-16 19:23:13
