Methods to summarize Generalized Linear Models fits
summary method for the class 'speedglm'.
## 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,...)
object |
an object of class 'speedglm'. |
correlation |
logical. Do you want to print the correlation matrix? By default it is false. |
... |
further optional arguments |
coefficients |
the matrix of coefficients, standard errors, z-statistics and two-side p-values. |
df.residual |
the component from object. |
df.null |
the component from object. |
null.deviance |
the component from object. |
deviance |
the component from object. |
family |
the component from object. |
call |
the component from object. |
AIC |
the Akaike Information Criterion. |
RSS |
Residuals sums of squares. |
correlation |
(only if |
logLik |
the log-likelihood value. |
rank |
the component from object. |
dispersion |
the estimated dispersion parameter of the fitted model. |
convergence |
the component from object. |
iter |
the component from object. |
tol |
the component from object. |
Marco ENEA
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.