summary.glm(stats)
summary.glm()所属R语言包：stats
Summarizing Generalized Linear Model Fits
总结广义线性模型的适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
These functions are all methods for class glm or summary.glm objects.
这些功能是所有methods类glm或summary.glm对象。
用法----------Usage----------
## S3 method for class 'glm'
summary(object, dispersion = NULL, correlation = FALSE,
symbolic.cor = FALSE, ...)
## S3 method for class 'summary.glm'
print(x, digits = max(3, getOption("digits") - 3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class "glm", usually, a result of a call to glm.
一个类的对象"glm"，通常，调用glm的结果。
参数：x
an object of class "summary.glm", usually, a result of a call to summary.glm.
一个类的对象"summary.glm"，通常，调用summary.glm的结果。
参数：dispersion
the dispersion parameter for the family used. Either a single numerical value or NULL (the default), when it is inferred from object (see "Details").
分散的家庭使用的参数。无论是单一数值或NULL（默认值），当它被推断object（见“详细资料”）。
参数：correlation
logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
逻辑; TRUE如果，估计参数的相关矩阵，则返回并打印。
参数：digits
the number of significant digits to use when printing.
打印时使用的有效位数的号码。
参数：symbolic.cor
logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.
逻辑。如果TRUE，在一个象征性的形式打印的相关性（见symnum），而不是数字。
参数：signif.stars
logical. If TRUE, "significance stars" are printed for each coefficient.
逻辑。如果TRUE，意义恒星的印有每个系数。
参数：...
further arguments passed to or from other methods.
通过进一步的论据或其他方法。
Details
详情----------Details----------
print.summary.glm tries to be smart about formatting the coefficients, standard errors, etc. and additionally gives "significance stars" if signif.stars is TRUE. The coefficients component of the result gives the estimated coefficients and their estimated standard errors, together with their ratio. This third column is labelled t ratio if the dispersion is estimated, and z ratio if the dispersion is known (or fixed by the family). A fourth column gives the two-tailed p-value corresponding to the t or z ratio based on a Student t or Normal reference distribution. (It is possible that the dispersion is not known and there are no residual degrees of freedom from which to estimate it. In that case the estimate is NaN.)
print.summary.glm尝试聪明格式化的系数，标准误差等，另外给“意义星”signif.stars如果是TRUE的。 coefficients结果的组成部分，给出的估计系数和估计标准误差，连同他们的比率。第三列标记t ratio如果分散预计，和z ratio如果被称为色散（或家庭固定）。第四列给出的双尾P-值对应的t或Z比基于学生t或正常参考分布。 （这是可能的分散不知道有自由无残留度估计。在这种情况下，估计是NaN。）
Aliased coefficients are omitted in the returned object but restored by the print method.
在返回的对象锯齿系数被省略，但恢复print方法。
Correlations are printed to two decimal places (or symbolically): to see the actual correlations print summary(object)$correlation directly.
相关印两个小数（或符号）：看实际相关打印summary(object)$correlation直接。
The dispersion of a GLM is not used in the fitting process, but it is needed to find standard errors. If dispersion is not supplied or NULL, the dispersion is taken as 1 for the binomial and Poisson families, and otherwise estimated by the residual Chisquared statistic (calculated from cases with non-zero weights) divided by the residual degrees of freedom.
在装修过程中不使用的GLM的分散，但它需要找到标准的错误。如果dispersion不提供或NULL，分散1的binomial和Poisson家庭，否则估计剩余Chisquared统计（计算自由残余度的划分与非零权重的情况下）。
summary can be used with Gaussian glm fits to handle the case of a linear regression with known error variance, something not handled by summary.lm.
summary可以使用高斯glm适合于处理与已知的误差方差的线性回归的情况下，一些不summary.lm处理。
值----------Value----------
summary.glm returns an object of class "summary.glm", a list with components
summary.glm类"summary.glm"，列表中的对象与组件返回
参数：call
the component from object.
object组成部分。
参数：family
the component from object.
object组成部分。
参数：deviance
the component from object.
object组成部分。
参数：contrasts
the component from object.
object组成部分。
参数：df.residual
the component from object.
object组成部分。
参数：null.deviance
the component from object.
object组成部分。
参数：df.null
the component from object.
object组成部分。
参数：deviance.resid
the deviance residuals: see residuals.glm.
偏差残差：看到residuals.glm。
参数：coefficients
the matrix of coefficients, standard errors, z-values and p-values. Aliased coefficients are omitted.
矩阵系数，标准误差，z值和p值。抗锯齿系数省略。
参数：aliased
named logical vector showing if the original coefficients are aliased.
命名逻辑的向量，如果原来的系数别名。
参数：dispersion
either the supplied argument or the inferred/estimated dispersion if the latter is NULL.
提供的参数或分散推断/估计，如果后者是NULL。
参数：df
a 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of non-aliased coefficients.
3矢量模型和残留程度的自由，加上非失真系数的数量级。
参数：cov.unscaled
the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.
未缩放（dispersion = 1）的估计系数的协方差矩阵的估计。
参数：cov.scaled
ditto, scaled by dispersion.
同上，dispersion缩放。
参数：correlation
(only if correlation is true.) The estimated correlations of the estimated coefficients.
（只有correlation是真实的。）的估计系数的估计相关。
参数：symbolic.cor
(only if correlation is true.) The value of the argument symbolic.cor.
（只有correlation是真实的。）值参数symbolic.cor。
参见----------See Also----------
glm, summary.
glm，summary。
举例----------Examples----------
## For examples see example(glm)[＃例如对于例子（GLM）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
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发表于 2012-2-16 19:55:57
