summary.lm(stats)
summary.lm()所属R语言包：stats
Summarizing Linear Model Fits
总结线性模型适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
summary method for class "lm".
summary类"lm"方法。
用法----------Usage----------
## S3 method for class 'lm'
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'summary.lm'
print(x, digits = max(3, getOption("digits") - 3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class "lm", usually, a result of a call to lm.
一个类的对象"lm"，通常，调用lm的结果。
参数：x
an object of class "summary.lm", usually, a result of a call to summary.lm.
一个类的对象"summary.lm"，通常，调用summary.lm的结果。
参数：correlation
logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
逻辑; TRUE如果，估计参数的相关矩阵，则返回并打印。
参数：digits
the number of significant digits to use when printing.
打印时使用的有效位数的号码。
参数：symbolic.cor
logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.
逻辑。如果TRUE，在一个象征性的形式打印的相关性（见symnum），而不是数字。
参数：signif.stars
logical. If TRUE, "significance stars" are printed for each coefficient.
逻辑。如果TRUE，意义恒星的印有每个系数。
参数：...
further arguments passed to or from other methods.
通过进一步的论据或其他方法。
Details
详情----------Details----------
print.summary.lm tries to be smart about formatting the coefficients, standard errors, etc. and additionally gives "significance stars" if signif.stars is TRUE.
print.summary.lm尝试聪明格式化的系数，标准误差等，另外给“意义星”signif.stars如果是TRUE的。
Correlations are printed to two decimal places (or symbolically): to see the actual correlations print summary(object)$correlation directly.
相关印两个小数（或符号）：看实际相关打印summary(object)$correlation直接。
值----------Value----------
The function summary.lm computes and returns a list of summary statistics of the fitted linear model given in object, using the components (list elements) "call" and "terms" from its argument, plus
函数summary.lm计算并返回一个列表object给定的模型拟合线性的汇总统计，从它的参数使用的组件（列表元素）"call"和"terms"加
参数：residuals
the weighted residuals, the usual residuals rescaled by the square root of the weights specified in the call to lm.
加权残值法，通常残差平方根的调用lm在指定的权重重新调整。
参数：coefficients
a p x 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value. Aliased coefficients are omitted.
p x 4矩阵的估计系数，标准误差，t-统计量和相应的（双面）p值的列。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：sigma
the square root of the estimated variance of the random error <p align="center">σ^2 = 1/(n-p) Sum(w[i] R[i]^2), where R[i] is the i-th residual, residuals[i].
随机误差的估计方差的平方根<p ALIGN="CENTER">σ^2 = 1/(n-p) Sum(w[i] R[i]^2),其中R[i]日剩余i，residuals[i]。
参数：df
degrees of freedom, a 3-vector (p, n-p, p*), the last being the number of non-aliased coefficients.
自由度，3向量(p, n-p, p*)，最后是一些非失真系数。
参数：fstatistic
(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
（包括非截距模型）3向量F-统计值与它的分子和分母的自由程度。
参数：r.squared
R^2, the "fraction of variance explained by the model", <p align="center">R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2), where y* is the mean of y[i] if there is an intercept and zero otherwise.
R^2，“分数的方差模型解释”，<p ALIGN="CENTER">R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2),其中y*y[i]的平均值，如果有一个拦截，否则为零。
参数：adj.r.squared
the above R^2 statistic "adjusted", penalizing for higher p.
上述惩罚更高R^2 p统计调整，。
参数：cov.unscaled
a p x p matrix of (unscaled) covariances of the coef[j], j=1, …, p.
，p x p，coef[j]j=1, …, p矩阵（未缩放）方差。
参数：correlation
the correlation matrix corresponding to the above cov.unscaled, if correlation = TRUE is specified.
对应上面的相关矩阵cov.unscaled如果correlation = TRUE指定。
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。
参数：na.action
from object, if present there.
从object，如果目前有。
参见----------See Also----------
The model fitting function lm, summary.
该模型的拟合函数lm，summary。
Function coef will extract the matrix of coefficients with standard errors, t-statistics and p-values.
功能coef将提取的标准误，t-统计量和p值的系数矩阵。
举例----------Examples----------
##-- Continuing the lm(.) example:[ - 持续的LM例如：（）。]
coef(lm.D90)# the bare coefficients[裸系数]
sld90 <- summary(lm.D90 <- lm(weight ~ group -1))# omitting intercept[省略拦截]
sld90
coef(sld90)# much more[更]
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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 2012-2-16 18:07:12
