lm.summaries(stats)
lm.summaries()所属R语言包：stats
Accessing Linear Model Fits
访问线性模型适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
All these functions are methods for class "lm" objects.
所有这些功能都methods类"lm"对象。
用法----------Usage----------
## S3 method for class 'lm'
family(object, ...)
## S3 method for class 'lm'
formula(x, ...)
## S3 method for class 'lm'
residuals(object,
type = c("working", "response", "deviance", "pearson",
"partial"),
...)
## S3 method for class 'lm'
labels(object, ...)
参数----------Arguments----------
参数：object, x
an object inheriting from class lm, usually the result of a call to lm or aov.
从类对象继承lm，通常是一个lm或aov调用的结果。
参数：...
further arguments passed to or from other methods.
通过进一步的论据或其他方法。
参数：type
the type of residuals which should be returned.
应当返还的残差类型。
Details
详情----------Details----------
The generic accessor functions coef, effects, fitted and residuals can be used to extract various useful features of the value returned by lm.
通用存取功能coef，effects，fitted和residuals可用于提取各种有用的功能由lm返回的值。
The working and response residuals are "observed - fitted". The deviance and pearson residuals are weighted residuals, scaled by the square root of the weights used in fitting. The partial residuals are a matrix with each column formed by omitting a term from the model. In all these, zero weight cases are never omitted (as opposed to the standardized rstudent residuals, and the weighted.residuals).
工作和响应残差观察 - 装“。偏差和Pearson残差加权残值，在装修中使用的重量平方根缩放。部分残差模型省略长期形成的每一列的矩阵。在所有这些，是从来没有省略零重量箱（标准化rstudent残差，而不是weighted.residuals）。
How residuals treats cases with missing values in the original fit is determined by the na.action argument of that fit. If na.action = na.omit omitted cases will not appear in the residuals, whereas if na.action = na.exclude they will appear, with residual value NA. See also naresid.
如何residuals将缺失值的情况下，在原适合确定na.action合身的说法的。如果na.action = na.omit省略的情况下将不会出现在残差，而如果na.action = na.exclude“他们会出现剩余价值NA。还可以看naresid。
The "lm" method for generic labels returns the term labels for estimable terms, that is the names of the terms with an least one estimable coefficient.
"lm"通用labels方法返回为难能可贵方面的长期的标签，这是一个至少有一个估系数的条款名称。
参考文献----------References----------
Linear models. Chapter 4 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
参见----------See Also----------
The model fitting function lm, anova.lm.
该模型的拟合函数lm，anova.lm。
coef, deviance, df.residual, effects, fitted, glm for generalized linear models, influence (etc on that page) for regression diagnostics, weighted.residuals, residuals, residuals.glm, summary.lm, weights.
coef，deviance，df.residual，effects，fitted，glm广义线性模型，influence（等上该网页）回归诊断，weighted.residuals，residuals，residuals.glm，summary.lm，weights。
influence.measures for deletion diagnostics, including standardized (rstandard) and studentized (rstudent) residuals.
influence.measures缺失诊断，包括标准化（rstandard）和学生化（rstudent）残差。
举例----------Examples----------
##-- Continuing the lm(.) example:[ - 持续的LM例如：（）。]
coef(lm.D90)# the bare coefficients[裸系数]
## The 2 basic regression diagnostic plots [plot.lm(.) is preferred][＃2基本回归诊断图plot.lm（）。首选]]
plot(resid(lm.D90), fitted(lm.D90))# Tukey-Anscombe's[杜克-安斯库姆的]
abline(h=0, lty=2, col = 'gray')
qqnorm(residuals(lm.D90))
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 2012-2-16 19:28:38
