summary.speedglm(speedglm)
summary.speedglm()所属R语言包：speedglm
Methods to summarize Generalized Linear Models fits
总结广义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 the class 'speedglm'.
summary方法类的speedglm“。
用法----------Usage----------
## S3 method for class 'speedglm':
summary(object,correlation=FALSE,...)
## S3 method for class 'speedglm':
coef(object,...)
## S3 method for class 'speedglm':
vcov(object,...)
## S3 method for class 'speedglm':
logLik(object,...)
## S3 method for class 'speedglm':
AIC(object,...)
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：...
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, z-statistics and two-side p-values.</td></tr> <tr valign="top"><td>df.residual</td> <td> the component from object.</td></tr> <tr valign="top"><td>df.null</td> <td> the component from object.</td></tr> <tr valign="top"><td>null.deviance</td> <td> the component from object.</td></tr> <tr valign="top"><td>deviance</td> <td> the component from object.</td></tr> <tr valign="top"><td>family</td> <td> the component from object.</td></tr> <tr valign="top"><td>call</td> <td> the component from object.</td></tr> <tr valign="top"><td>AIC</td> <td> the Akaike Information Criterion.</td></tr> <tr valign="top"><td>RSS</td> <td> Residuals sums of squares.</td></tr> <tr valign="top"><td>correlation</td> <td> (only if correlation is true.) The correlations of the estimated coefficients.</td></tr> <tr valign="top"><td>logLik</td> <td> the log-likelihood value.</td></tr> <tr valign="top"><td>rank</td> <td> the component from object.</td></tr> <tr valign="top"><td>dispersion</td> <td> the estimated dispersion parameter of the fitted model.</td></tr> <tr valign="top"><td>convergence</td> <td> the component from object.</td></tr> <tr valign="top"><td>iter</td> <td> the component from object.</td></tr> <tr valign="top"><td>tol</td> <td> the component from object.</td></tr>
<table summary="R valueblock"> <tr valign="top"> <TD> coefficients</ TD> <TD>的系数矩阵，标准差，Z统计和两个侧P-值</ TD> </ TR> <tr valign="top"> <TD> df.residual</ TD> <TD>对象的组件。</ TD> </ TR> <TR VALIGN =“顶“<TD> df.null </ TD> <TD>对象的组件。</ TD> </ TR> <tr valign="top"> <TD>null.deviance</ TD > <TD>的组件对象。</ TD> </ TR> <tr valign="top"> <TD> deviance </ TD> <TD>组件对象。</ TD> < / TR> <tr valign="top"> <TD> family </ TD> <TD>对象的组件。</ TD> </ TR> <tr valign="top"> <TD> call</ TD> <TD>对象的组件。</ TD> </ TR> <tr valign="top"> <TD>AIC </ TD> <TD>的Akaike信息准则。</ TD> </ TR> <tr valign="top"> <TD>RSS </ TD> <TD>残差平方和。</ TD> </ TR> <TR VALIGN =“顶”> <TD>correlation </ TD> <TD>（只有correlation是真实的。）的估计系数的相关性。</ TD> </ TR> <TR VALIGN =“”> <TD>logLik </ TD> <TD>对数似然值。</ TD> </ TR> <tr valign="top"> <TD>rank </ TD> <TD>对象的组件。</ TD> </ TR> <tr valign="top"> <TD>dispersion </ TD> <TD>估计分散的拟合参数模型。</ TD> </ TR> <tr valign="top"> <TD>convergence</ TD> <TD>对象的组件。</ TD> </ TR> <TR VALIGN “顶”> <TD> iter </ TD> <TD>对象的组件。</ TD> </ TR> <tr valign="top"> <TD>tol</ TD> <TD>对象的组件。</ TD> </ TR>
</table>
</ TABLE>
（作者）----------Author(s)----------
Marco ENEA
参见----------See Also----------
speedglm
speedglm
实例----------Examples----------
n<-1000
k<-5
y <- rgamma(n,1.5,1)
x <-round( matrix(rnorm(n*k),n,k),digits=3)
colnames(x) <-paste("s",1:k,sep = "")
da<- data.frame(y,x)
fo <- as.formula(paste("y~",paste(paste("s",1:k,sep=""),collapse="+")))
m4 <- speedglm(fo,data=da,family=Gamma(log))
summary(m4)
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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 2012-9-30 14:55:30
