wle.lm.summaries(wle)
wle.lm.summaries()所属R语言包：wle
Accessing Linear Model Fits for wle.lm
访问线性模型适用于wle.lm
译者：生物统计家园网 机器人LoveR
描述----------Description----------
All these functions are methods for class wle.lm or summary.wle.lm.
所有这些功能是methods类wle.lm或summary.wle.lm。
用法----------Usage----------
## S3 method for class 'wle.lm':
coef(object, ...)
## S3 method for class 'wle.lm':
formula(x, ...)
## S3 method for class 'wle.lm':
fitted(object, ...)
## S3 method for class 'wle.lm':
model.frame(formula, data, na.action, ...)
## S3 method for class 'wle.lm':
summary(object, root="ALL", ...)
## S3 method for class 'wle.lm.root':
summary(object, root=1, ...)
## S3 method for class 'wle.lm':
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'summary.wle.lm':
print(x, digits = max(3, getOption("digits") - 3),
signif.stars= getOption("show.signif.stars"), ...)
## S3 method for class 'summary.wle.lm.root':
print(x, digits = max(3, getOption("digits") - 3),
signif.stars= getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class wle.lm.
对象类wle.lm。
参数：x
an object of class wle.lm or summary.wle.lm.
对象的类wle.lm或summary.wle.lm。
参数：formula
a model formula
模型公式
参数：data
data.frame, list, environment or object coercible to data.frame containing the variables in formula.
data.frame，列表，environment或对象强制转换data.frame中的变量formula。
参数：na.action
how NAs are treated. The default is first, any na.action attribute of data, second a na.action setting of options, and third na.fail if that is unset. The “factory-fresh” default is na.omit.
如何NAs的处理。默认的是：第一，任何na.action属性data，第二个是na.action的options，和第三na.fail，如果是没有设置的。 “出厂时的默认是na.omit。
参数：root
the root to be printed, in summary.wle.lm it could be "ALL", all the roots are printed, or a vector of integers.
要打印的根，它可能是在summary.wle.lm“ALL（全部）”，所有的根被打印，或一个矢量的整数。
参数：digits
number of digits to be used for most numbers.
用于大多数数字的位数数。
参数：signif.stars
logical; if TRUE, P-values are additionally encoded visually as “significance stars” in order to help scanning of long coefficient tables. It defaults to the show.signif.stars slot of options.
逻辑，如果TRUE，P-值额外编码的视觉“的意义星星”，以帮助长系数表扫描。默认为show.signif.stars插槽options。
参数：...
additional arguments.
其他参数。
Details
详细信息----------Details----------
print.summary.wle.lm and print.summary.wle.lm.root tries formatting for each root the coefficients, standard errors, etc. and additionally gives “significance stars” if signif.stars is TRUE.
print.summary.wle.lm和print.summary.wle.lm.root尝试格式化为每根系数，标准误差和意义还给出了“明星”，如果signif.stars是TRUE。
The generic accessor functions coefficients, fitted.values, residuals and weights can be used to extract various useful features of the value returned by wle.lm.
一般的访问功能coefficients，fitted.values，residuals和weights可以用于提取各种有用的功能的wle.lm返回的值。
值----------Value----------
The function summary.wle.lm (the summary.wle.lm.root do the same for just one selected root) computes and returns, for each selected root, 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
的功能summary.wle.lm（summary.wle.lm.root做同样的只是一个选定的根）计算并返回，为每个选定的根目录，列表的汇总统计数据的拟合线性模型在object使用的组件（列表中的元素）"call"和"terms"从它的参数，加
<table summary="R valueblock"> <tr valign="top"><td>residuals</td> <td> the weighted residuals, the usual residuals rescaled by the square root of the weights given by wle.lm.</td></tr> <tr valign="top"><td>coefficients</td> <td> a p x 4 matrix with columns for the estimated coefficient, its standard error, weighted-t-statistic and corresponding (two-sided) p-value.</td></tr> <tr valign="top"><td>sigma</td> <td> the square root of the estimated variance of the random error.</td></tr> <tr valign="top"><td>df</td> <td> degrees of freedom, a 3-vector (p, ∑{weights} - p, p*).</td></tr> <tr valign="top"><td>fstatistic</td> <td> a 3-vector with the value of the weighted-F-statistic with its numerator and denominator degrees of freedom.</td></tr> <tr valign="top"><td>r.squared</td> <td> R^2, the “fraction of variance explained by the model”.</td></tr> <tr valign="top"><td>adj.r.squared</td> <td> the above R^2 statistic “adjusted”, penalizing for higher p.</td></tr> <tr valign="top"><td>root</td> <td> the label of the root reported.</td></tr>
<table summary="R valueblock"> <tr valign="top"> <TD>residuals </ TD> <TD>的加权残值法，通常的残差重新调整权重的平方根的 wle.lm。</ TD> </ TR> <tr valign="top"> <TD>coefficients </ TD> <td>一个p x 4的估计系数矩阵的列，其标准错误，加权t-统计量和相应的（双面）P-值</ TD> </ TR> <tr valign="top"> <TD>sigma </ TD> <TD。随机误差的估计方差的平方根。</ TD> </ TR> <tr valign="top"> <TD>df </ TD> <TD>自由度，3 - 矢量(p, ∑{weights} - p, p*)。</ TD> </ TR> <tr valign="top"> <TD> fstatistic </ TD> <td>一个3矢量的值的加权， F-统计量的分子和分母自由度。</ TD> </ TR> <tr valign="top"> <TD>r.squared </ TD> <TD>R^2， “分数的方差模型解释”。</ TD> </ TR> <tr valign="top"> <TD>adj.r.squared </ TD> <TD>上面的R^2统计“调整”，惩罚p。</ TD> </ TR> <tr valign="top"> <TD>root </ TD> <TD>的标签的根报告</ TD> </ TR>
</table>
</ TABLE>
（作者）----------Author(s)----------
Claudio Agostinelli
参见----------See Also----------
wle.lm a function for estimating linear models with normal distribution error and normal kernel, plot.wle.lm for plot method.
wle.lm估计线性模型与正常分配错误和正常的内核，plot.wle.lm图法的功能。
实例----------Examples----------
library(wle)
# You can find this data set in:[你可以找到这个数据集：]
# Hawkins, D.M., Bradu, D., and Kass, G.V. (1984). [霍金斯位于Bradu，D.M.，，D.，卡斯，G.V.的（1984）。]
# Location of several outliers in multiple regression data using[在多元回归分析数据，使用几个离群的位置]
# elemental sets. Technometrics, 26, 197-208.[元素集。品质管理，26，197-208。]
#[]
data(artificial)
result <- wle.lm(y.artificial~x.artificial,boot=40,group=6,num.sol=3)
#summary only for the first root[总结的第一根]
summary(result,root=1)
#summary for all the roots[总结所有的根]
summary(result,root="ALL")
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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 2012-10-1 22:40:02
