summary.speedlm(speedglm)
summary.speedlm()所属R语言包：speedglm
Methods to summarize Linear Models fits
总结线性模型的方法适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
summary method for class 'speedlm'.
summary方法为类的speedlm“的。
用法----------Usage----------
## S3 method for class 'speedlm':
summary(object, correlation = FALSE,...)
## S3 method for class 'speedlm':
coef(object,...)
## S3 method for class 'speedlm':
vcov(object,...)
## S3 method for class 'speedlm':
logLik(object,...)
## S3 method for class 'speedlm':
AIC(object,...,k = 2)
参数----------Arguments----------
参数：object
an object of class 'speedlm'.
对象类的speedlm。
参数：correlation
logical. Do you want to print the correlation matrix? By default it is false.
逻辑。你要打印的相关系数矩阵？默认情况下，它是假的。
参数：k
numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.
k = 2的数字，加罚参数使用;默认的是经典的AIC。
参数：...
further optional arguments
进一步的可选参数
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>coefficients</td> <td> the matrix of coefficients, standard errors, t-statistics and two-side p-values.</td></tr> <tr valign="top"><td>rdf</td> <td> degrees of freedom of the fitted model. It is a component from object.</td></tr> <tr valign="top"><td>call</td> <td> the component from object.</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 "adjusted" R^2 statistic, penalizing for higher p.</td></tr> <tr valign="top"><td>fstatistic</td> <td> (for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.</td></tr> <tr valign="top"><td>f.pvalue</td> <td> p-value of the F-statistic.</td></tr> <tr valign="top"><td>RSS</td> <td> Residual sum of squares.</td></tr> <tr valign="top"><td>var.res</td> <td> estimated variance of residuals.</td></tr> <tr valign="top"><td>rank</td> <td> the component from object.</td></tr> <tr valign="top"><td>correlation</td> <td> (only if correlation is true) the correlations of the estimated parameters.</td></tr> <tr valign="top"><td>...</td> <td> the results from the functions logLik, AIC and vcov.</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> coefficients</ TD> <TD>的系数矩阵，标准差，t-统计和两个侧P-值</ TD> </ TR> <tr valign="top"> <TD>rdf </ TD> <TD>程度的自由的拟合模型。这是一个组件从object。</ TD> </ TR> <tr valign="top"> <TD>call </ TD> <TD>组件object </ 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>“调整”R ^ 2统计，惩罚较高的P。</ TD> </ TR> <TR VALIGN =“”> <TD>fstatistic </ TD> <TD>（包括非截距项的模型）3向量的F-统计量的值与它的分子和分母自由度</ TD> </ TR> <tr valign="top"> <TD>f.pvalue </ TD> <TD>的F-统计量的p值</ TD> </ TR> < TR VALIGN =“顶”> <TD>RSS </ TD> <TD>残差平方和。</ TD> </ TR> <tr valign="top"> <TD>var.res </ TD> <TD>估计残差的方差。</ TD> </ TR> <tr valign="top"> <TD>rank </ TD> <TD>组件从<X ></ TD> </ TR> <tr valign="top"> <TD>object </ TD> <TD>（只有correlation是真实的）的相关性的估计参数。</ TD> </ TR> <tr valign="top"> <TD>correlation </ TD> <TD>结果从功能...，logLik AIC。</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Marco ENEA
参见----------See Also----------
speedlm
speedlm
实例----------Examples----------
y <- rnorm(100,1.5,1)
x <- round(matrix(rnorm(200), 100, 2), digits = 3)
colnames(x) <- c("s1","s2")
da <- data.frame(y, x)
m <- speedlm(y ~ s1 + s2,da)
summary(m)
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。
|
发表于 2012-9-30 14:55:38
