lm.influence(stats)
lm.influence()所属R语言包：stats
Regression Diagnostics
回归诊断
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function provides the basic quantities which are used in forming a wide variety of diagnostics for checking the quality of regression fits.
此功能提供了用于形成各种各样的回归配合的质量检查诊断的基本数量。
用法----------Usage----------
influence(model, ...)
## S3 method for class 'lm'
influence(model, do.coef = TRUE, ...)
## S3 method for class 'glm'
influence(model, do.coef = TRUE, ...)
lm.influence(model, do.coef = TRUE)
参数----------Arguments----------
参数：model
an object as returned by lm or glm.
作为一个对象返回lm或glm。
参数：do.coef
logical indicating if the changed coefficients (see below) are desired. These need O(n^2 p) computing time.
如果改变coefficients（见下文）所需的逻辑表明。这些都需要O(n^2 p)计算时间。
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----------
The influence.measures() and other functions listed in See Also provide a more user oriented way of computing a variety of regression diagnostics. These all build on lm.influence. Note that for GLMs (other than the Gaussian family with identity link) these are based on one-step approximations which may be inadequate if a case has high influence.
influence.measures()和其他在看到所列出的函数还提供了更多的用户导向的方式计算各种回归诊断。这些都建立在lm.influence。请注意，这些都是一步逼近，这可能是不足的情况下，如果具有很高的影响力为基础GLMs（高斯家庭以外的身份链接）。
An attempt is made to ensure that computed hat values that are probably one are treated as one, and the corresponding rows in sigma and coefficients are NaN. (Dropping such a case would normally result in a variable being dropped, so it is not possible to give simple drop-one diagnostics.)
企图，以确保计算机的帽子，可能是一个作为一个治疗价值，并在相应的行sigma和coefficients是NaN。 （删除这种情况下通常会导致被丢弃的变量，所以给简单的下拉一个诊断，这是不可能的。）
naresid is applied to the results and so will fill in with NAs it the fit had na.action = na.exclude.
naresid结果，将填补NA的适合na.action = na.exclude。
值----------Value----------
A list containing the following components of the same length or number of rows n, which is the number of non-zero weights. Cases omitted in the fit are omitted unless a na.action method was used (such as na.exclude) which restores them.
一个列表，其中包含以下组件的长度相同或行数n，这是非零重量。除非na.action方法是使用（na.exclude等），恢复他们在适当的省略的情况下被省略。
参数：hat
a vector containing the diagonal of the "hat" matrix.
矢量包含的帽子矩阵的对角线。
参数：coefficients
(unless do.coef is false) a matrix whose i-th row contains the change in the estimated coefficients which results when the i-th case is dropped from the regression. Note that aliased coefficients are not included in the matrix.
（除非do.coef是假的）一个矩阵的第i行中包含的结果时，第i情况件下降回归估计系数的变化。注意别名系数不包括在矩阵。
参数：sigma
a vector whose i-th element contains the estimate of the residual standard deviation obtained when the i-th case is dropped from the regression. (The approximations needed for GLMs can result in this being NaN.)
一个向量，其第i个元素包含回归下降时获得的第i情况件的残留标准偏差估计。 （需要为GLMs近似可能导致这是NaN）。
参数：wt.res
a vector of weighted (or for class glm rather deviance) residuals.
一个加权的矢量（或类glm而越轨）残差。
注意----------Note----------
The coefficients returned by the R version of lm.influence differ from those computed by S. Rather than returning the coefficients which result from dropping each case, we return the changes in the coefficients. This is more directly useful in many diagnostic measures.<br> Since these need O(n^2 p) computing time, they can be omitted by do.coef = FALSE.
coefficientslm.influence从计算的不同，所学而不是返回系数导致辍学每一种情况下，我们回归系数的变化，由R版本返回。这是更直接有用的许多诊断措施。参考O(n^2 p)计算时间由于这些需要，他们可以通过do.coef = FALSE省略。
Note that cases with weights == 0 are dropped (contrary to the situation in S).
注意：以weights == 0情况都将被丢弃（相反的情况）。
If a model has been fitted with na.action=na.exclude (see na.exclude), cases excluded in the fit are considered here.
如果模型已经配备了na.action=na.exclude（见na.exclude），排除在合适的情况下被认为是在这里。
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----------
summary.lm for summary and related methods;<br> influence.measures,<br> hat for the hat matrix diagonals,<br> dfbetas, dffits, covratio, cooks.distance, lm.
summary.lmsummary和相关的方法;参考influence.measures参考hat的帽子矩阵对角线，参考dfbetas，<X >，dffits，covratio，cooks.distance。
举例----------Examples----------
## Analysis of the life-cycle savings data[＃生命周期储蓄数据的分析]
## given in Belsley, Kuh and Welsch.[＃给予Belsley山和韦尔施。]
summary(lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi,
data = LifeCycleSavings),
corr = TRUE)
utils::str(lmI <- lm.influence(lm.SR))
## For more "user level" examples, use example(influence.measures)[＃“用户级别”的例子，使用的例子（influence.measures）]
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。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-16 20:36:44
